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Homework 3 Notebook for Tim Cogley's course
Raw
HW3Notebook
{
"metadata": {
"celltoolbar": "Slideshow",
"language": "Julia",
"name": "",
"signature": "sha256:48c93e55dd13e85a8b1e797778a71d47dfe8f59cbe53a02778db64f6eacaad7a"
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"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Homework 3: Simplified Stock and Watson\n",
"\n",
"<br>\n",
"<br>\n",
"<br>\n",
"<br>\n",
"<br>\n",
"<br>\n",
"<br>\n",
"<br>\n",
"\n",
"<style>\n",
"h3 {text-align:center;}\n",
"p {text-align:center;}\n",
"</style>\n",
"\n",
"<h3>\n",
"Class: Empirical Methods for Dynamic Macroeconomics\n",
"<br>\n",
"Instructor: Tim Cogley\n",
"<br>\n",
"Author: Chase Coleman\n",
"</h3>"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Model\n",
"\n",
"Our model of inlation is the following:\n",
"\n",
" $$ \\tau_t = \\tau_{t-1} + \\varepsilon_{\\tau, t} $$\n",
" $$ \\pi_t = \\tau_t + \\varepsilon_{\\pi, t} $$\n",
"\n",
"where $\\varepsilon_{\\pi, t} \\sim N(0, \\sigma^2_\\pi)$ and $\\varepsilon_{\\pi, t} \\sim N(0, \\sigma^2_\\tau)$.\n",
"\n",
"The ultimate goal is to use post war (September 2, 1945 was end of war) inflation data from the U.S. to simulate the posterior of the model parameters $\\sigma_\\pi^2, \\sigma_\\tau^2, \\tau^T$.\n",
"\n",
"We will proceed in 3 main sections:\n",
"\n",
" * Gibbs Theory\n",
" - Blocking Parameters\n",
" * Algorithm Design\n",
" - Basic Design\n",
" - Difficulties\n",
" * Computations"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Gibbs Theory\n",
"\n",
"The Gibbs sampler is a special case of the Metropolis-Hastings algorithm (which in turn is a special case of the Metropolis algorithm). It is a special case for when we are able to draw from fully conditional distributions.\n",
"\n",
"In our problem, we would like to find:\n",
"\n",
"$$ f \\left(\\sigma_\\pi^2, \\sigma_\\tau^2, \\tau^T, \\pi^T \\right) $$\n",
"\n",
"where $\\pi^T$ is the inflation data that we observe. We will get draws from this distribution by sampling from conditionals in three blocks:\n",
"\n",
"### Blocks\n",
"\n",
"*Block 1*: Draw $\\tau^T$ from $f \\left( \\tau^T | (\\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau) \\right)$\n",
"\n",
"*Block 2*: Draw $\\sigma^2_\\tau$ from $f \\left( \\sigma^2_\\tau | (\\pi^T, \\sigma^2_\\pi, \\tau^T) \\right)$\n",
"\n",
"*Block 3*: Draw $\\sigma^2_\\pi$ from $f \\left( \\sigma^2_\\pi | (\\pi^T, \\sigma^2_\\tau, \\tau^T) \\right)$\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Block 1: Sampling $\\tau^T$\n",
"\n",
"First notice the conditional posterior can be written as:\n",
"\n",
"$$ f \\left( \\tau^T | (\\sigma^2_\\tau, \\sigma^2_\\pi, \\pi^T)\\right) = f(\\tau^{T-1} | (\\tau_T, \\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) f(\\tau_T | (\\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) $$\n",
"$$ = f(\\tau^{T-2} | (\\tau_T, \\tau_{T-1}, \\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) f(\\tau_{T-1} | (\\tau_T, \\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) f(\\tau_T | (\\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) $$\n",
"$$ \\dots $$\n",
"$$= f(\\tau_T | (\\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) \\prod_{i=1}^{T-1} f(\\tau_{t-i} | (\\tau_{t - i + 1}, \\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)) $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Sampling Block 1\n",
"\n",
"To sample block 1, we need to use the forward filter backward sampler. This consists of two steps\n",
"\n",
" 1. Run the Kalman filter (to go forwards). This will tell us the probability of $\\tau_T$ given $(\\pi^T, \\sigma^2_\\pi, \\sigma^2_\\tau)$. We can then sample from $\\tau_T$ using $N(S_{t | t}, P_{t | t})$.\n",
" 2. Using $\\tau_T$ and the mean/covariance matrices generated by the Kalman filter, we sample backwards until we have the chain $\\tau^T$."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"\n",
"Author: Chase Coleman\n",
"Filename: lingaussSS_scalar.jl\n",
"\n",
"Here are several useful functions for working with the kalman filter.\n",
"\n",
"Note: These are scalar specific.\n",
"\n",
"TODO: Finish generalizing so that the helper functions can call either\n",
"the scalar or matrix versions of kalman_base.\n",
"\"\"\"\n",
"\n",
"function kalman_base(A::Float64, B::Float64, C::Float64, D::Float64,\n",
" data::Vector, S0::Float64, P0::Float64)\n",
"\n",
" (n_states, nobs) = 1, 1\n",
" T = size(data, 1)\n",
"\n",
" # ------------------------------------------------------------------- #\n",
" # Initialize\n",
" # ------------------------------------------------------------------- #\n",
" log_likelihood = Array(Float64, T)\n",
" Pt_tm1 = P0\n",
" Pt_t = P0\n",
" St_tm1 = S0\n",
" yt_tm1 = C*St_tm1\n",
" St_t = S0\n",
" Vt_tm1 = C*C*P0 + D*D\n",
" BB = B*B\n",
" DD = D*D\n",
"\n",
" Pt_tm1M = Array(Float64, T)\n",
" Pt_tM = Array(Float64, T)\n",
" St_tM = Array(Float64, T)\n",
"\n",
" for t=1:T\n",
" # Update the t given tm1 values and compute useful objects\n",
" St_tm1 = A * St_t # Update predicted state\n",
" yt_tm1 = C * St_tm1 # Update predicted observation\n",
" diffyt = data[t] - yt_tm1 # Measurement residual\n",
" Pt_tm1 = A*A*Pt_t + BB # Update State Variance\n",
" Vt_tm1 = C*C*Pt_tm1 + DD # Update Measurement Variance\n",
"\n",
" # Update LL\n",
" curr_ll = -.5 * (log(Vt_tm1) + diffyt*diffyt/Vt_tm1)\n",
" log_likelihood[t] = curr_ll\n",
"\n",
" # Update the t given t values\n",
" PCtVinv = Pt_tm1*C/Vt_tm1 # Compute useful object\n",
" St_t = St_tm1 + PCtVinv*diffyt # Update state | observation\n",
" Pt_t = Pt_tm1 - PCtVinv*C*Pt_tm1 # Update covariance | observation\n",
"\n",
" Pt_tm1M[t] = Pt_tm1\n",
" Pt_tM[t] = Pt_t\n",
" St_tM[t] = St_t\n",
"\n",
" end\n",
"\n",
" return Pt_tm1M, Pt_tM, St_tM, log_likelihood\n",
"end\n",
"\n",
"\n",
"function kalman_likelihood(A::Float64, B::Float64, C::Float64, D::Float64,\n",
" data::Vector, S0::Float64, P0::Float64)\n",
"\n",
" ll = kalman_base(A, B, C, D, data, S0, P0)[4]\n",
"\n",
" return sum(ll)\n",
"end\n",
"\n",
"\n",
"function kalman_history(A::Float64, B::Float64, C::Float64, D::Float64,\n",
" data::Vector, S0::Float64, P0::Float64)\n",
"\n",
" Pt_tm1, Pt_t, St_t = kalman_base(A, B, C, D, data, S0, P0)[1:3]\n",
"\n",
" return Pt_tm1, Pt_t, St_t\n",
"end\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 1,
"text": [
"kalman_history (generic function with 1 method)"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"function forward_backward_kalman_base(A::Float64, B::Float64, C::Float64, D::Float64,\n",
" data::Vector, S0::Float64, P0::Float64)\n",
"\n",
" (n_states, n_obs) = 1, 1\n",
" T = size(data, 1)\n",
"\n",
" # Allocate space\n",
" st_seq = Array(Float64, T)\n",
" St_tp1 = 0.\n",
" Pt_tp1 = 0.\n",
" loglikelihood = 0.\n",
"\n",
" # ---------------------------------------------------------------- #\n",
" # Execute Kalman Filter\n",
" # ---------------------------------------------------------------- #\n",
" Pt_tm1, Pt_t, St_t = kalman_history(A, B, C, D, data, S0, P0)\n",
"\n",
" # ---------------------------------------------------------------- #\n",
" # Backwards Sample\n",
" # ---------------------------------------------------------------- #\n",
" st_seq[end] = St_t[end] + Pt_t[end]*randn() # Draw from N(St_t, Pt_t)\n",
"\n",
" for t=T-1:-1:1\n",
" Ptp1_tinv = 1./Pt_tm1[t+1]\n",
" PtPtp1_tinv = Pt_t[t] * Ptp1_tinv\n",
"\n",
" St_tp1 = St_t[t] + PtPtp1_tinv * (st_seq[t+1] - St_t[t])\n",
" Pt_tp1 = Pt_t[t] - PtPtp1_tinv * Pt_t[t]\n",
"\n",
" st_seq[t] = St_tp1 + Pt_tp1*randn()\n",
"\n",
" curr_ll = -.5*(log(Pt_tp1) + (st_seq[t+1] - St_t[t]) * Ptp1_tinv * (st_seq[t+1] - St_t[t]))\n",
" loglikelihood = loglikelihood + curr_ll\n",
" end\n",
" return st_seq, loglikelihood\n",
"end\n",
"\n",
"function forward_backward_kalman_samp(A::Float64, B::Float64, C::Float64, D::Float64,\n",
" data::Vector, S0::Float64, P0::Float64)\n",
" return forward_backward_kalman_base(A, B, C, D, data, S0, P0)[1]\n",
"end\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"forward_backward_kalman_samp (generic function with 1 method)"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Block 2: Sampling $\\sigma^2_\\tau$\n",
"\n",
"Now notice the conditional posterior could also be written as:\n",
"\n",
"$$ f \\left( \\sigma^2_\\tau | (\\tau^T, \\sigma^2_\\pi, \\pi^T) \\right) = \\frac{f(\\sigma^2_\\tau) f(\\sigma^2_\\pi | \\sigma^2_\\tau) f( \\pi^T | (\\sigma^2_\\pi, \\sigma^2_\\tau) ) f( \\tau^T | (\\sigma^2_\\tau, \\sigma^2_\\pi, \\pi^T) )}{\\int_{\\sigma^2_\\tau} f(\\sigma^2_\\tau) f(\\sigma^2_\\pi | \\sigma^2_\\tau) f( \\pi^T | (\\sigma^2_\\pi, \\sigma^2_\\tau) ) f( \\tau^T | (\\sigma^2_\\tau, \\sigma^2_\\pi, \\pi^T) ) d \\sigma^2_\\tau} $$\n",
"$$ \\dots $$\n",
"$$ = f \\left( \\sigma^2_\\tau | \\tau^T \\right) $$\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Estimating $\\sigma^2_\\tau$ given $\\tau^T$ is very simple. We are simply estimating the variance of the innovations of $\\tau^T$ which are directly observed if we are given the history $\\tau^T$. Notice $\\varepsilon_t = \\tau_t - \\tau_{t-1} \\sim N(0, \\sigma^2_\\tau)$.\n",
"\n",
"Notice that this is a Gaussian random variable with known mean and unknown variance. If we impose an Inverse Gamma prior with parameters $\\alpha$ and $\\beta$ then this reduces to a Zellner problem with a posterior of Inverse Gamma with parameters $\\alpha + \\frac{T}{2}$ and $\\beta + \\frac{\\sum_t (\\tau_t - \\tau_{t-1})^2}{2}$."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"## Sampling Block 2\n",
"\n",
"To sample from block 2, we just draw a value from the Inverse Gamma distribution described in the previous slide."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Block 3: Sampling $\\sigma^2_\\pi$\n",
"\n",
"Now notice the conditional posterior could also be written as:\n",
"\n",
"$$ f \\left( \\sigma^2_\\pi | (\\tau^T, \\sigma^2_\\tau, \\pi^T) \\right) = \\frac{f(\\sigma^2_\\tau) f(\\sigma^2_\\pi | \\sigma^2_\\tau) f( \\pi^T, \\tau^T | (\\sigma^2_\\pi, \\sigma^2_\\tau) )}{\\int_{\\sigma^2_\\pi} f(\\sigma^2_\\tau) f(\\sigma^2_\\pi | \\sigma^2_\\tau) f( \\pi^T, \\tau^T | (\\sigma^2_\\pi, \\sigma^2_\\tau) ) d \\sigma^2_\\tau} $$\n",
"$$ \\dots $$\n",
"$$ = f \\left( \\sigma^2_\\pi | (\\tau^T, \\pi^T) \\right) $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Estimating $\\sigma^2_\\pi$ given $\\tau^T, \\pi^T$ is also simple. We are simply estimating the variance of the innovations of $\\pi^T$ which are directly observed if we are given the histories $\\pi^T, \\tau^T$. Notice $\\varepsilon_\\pi = \\pi_t - \\tau_t \\sim N(0, \\sigma^2_\\pi)$.\n",
"\n",
"Notice that this is a Gaussian random variable with known mean and unknown variance. If we impose an Inverse Gamma prior with parameters $\\alpha$ and $\\beta$ then this reduces to a Zellner problem with a posterior of Inverse Gamma with parameters $\\alpha + \\frac{T}{2}$ and $\\beta + \\frac{\\sum_t (\\pi_t - \\tau_t)^2}{2}$."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"## Sampling Block 3\n",
"\n",
"To sample block 3, we just draw a value from the Inverse Gamma distribution described in the previous slide."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Algorithm\n",
"\n",
"\n",
"## Gibbs Sampler\n",
"1. Choose priors for $\\tau_0$, $\\sigma^2_\\tau$, and $\\sigma^2_\\pi$\n",
"2. Until finished\n",
" * Sample from $\\tau^T$ conditional on knowing $\\sigma^2_\\pi, \\pi^T, \\sigma^2_\\tau$\n",
" * Sample from $\\sigma^2_\\tau$ conditional on knowing $\\tau^T$\n",
" * Sample from $\\sigma^2_\\pi$ conditional on knowing $\\tau^T, \\pi^T$\n",
"3. Check Convergence Criterion on Samples"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Algorithm Design Decisions\n",
"\n",
"Typically when I think about a computational problem, my best friend tends to be pen and paper. I often will write down some pseudo-code, derive some of the results that I need within my algorithm and only once I have spent some time thinking about the problem will I move to a computer. When I do move to a computer, I'll often write down a somewhat sloppy version of the code. This helps me see how each of the moving pieces work and helps me think about what design approach I should take.\n",
"\n",
"I don't always check this version for accuracy because it often gets erased once I am done writing a nicer version of my code. I then think about how to generalize the code and try to write a relatively general version that is more elegant than the previous version.\n",
"\n",
"Write a lot of different blocks and check that each of them are doing what you want it to. --Tim Cogley\n",
"\n",
"Try it on made up data where the answer is known. --Tom Sargent\n",
"\n",
"What do other people do?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"\n",
"This is a first go at writing the Gibbs Sampler for homework\n",
"assignment number 3 of Tim Cogley's Bayesian Methods course\n",
" \n",
"Notice that this is mostly a garbage version of the code.\n",
"\"\"\"\n",
"require(\"lingausSS.jl\")\n",
"using Distributions\n",
"\n",
"priors = Dict{Symbol, Distribution}()\n",
"priors[:\u03c4_0] = Normal(0, 1)\n",
"priors[:\u03c3_\u03c4] = InverseGamma(1, 2)\n",
"priors[:\u03c3_\u03c0] = InverseGamma(1, 2)\n",
"\n",
"infl = float64(readcsv(\"inflation_data.csv\")[:, 2])\n",
"\n",
"function gibbsme(prior::Dict, my_data::Array{Float64, 1}, nsamples=1000)\n",
"\n",
" nobs = size(my_data, 1)\n",
"\n",
" out_\u03c3_\u03c0 = Array(Float64, nsamples)\n",
" out_\u03c3_\u03c4 = Array(Float64, nsamples)\n",
" out_\u03c4_T = Array(Float64, nobs, nsamples)\n",
"\n",
" init_\u03c3_\u03c0 = rand(prior[:\u03c3_\u03c0])\n",
" init_\u03c3_\u03c4 = rand(prior[:\u03c3_\u03c4])\n",
" init_lgs = LinGausSS(1., init_\u03c3_\u03c4, 1., init_\u03c3_\u03c0)\n",
" init_\u03c4_T = forward_backward_kalman_samp(1., 1., init_\u03c3_\u03c4, init_\u03c3_\u03c0, my_data, 0., 0.)\n",
"\n",
" out_\u03c3_\u03c0[1] = init_\u03c3_\u03c0\n",
" out_\u03c3_\u03c4[1] = init_\u03c3_\u03c4\n",
" out_\u03c4_T[:, 1] = init_\u03c4_T\n",
"\n",
" for samp=2:nsamples\n",
"\n",
" out_\u03c4_T[:, samp] = block_tau(prior[:\u03c4_0], out_\u03c3_\u03c4[samp-1], out_\u03c3_\u03c0[samp-1], my_data)\n",
" out_\u03c3_\u03c4[samp] = block_sigtau(prior[:\u03c3_\u03c4], out_\u03c4_T[:, samp], out_\u03c3_\u03c0[samp-1])\n",
" out_\u03c3_\u03c0[samp] = block_sigpi(prior[:\u03c3_\u03c0], out_\u03c4_T[:, samp], out_\u03c3_\u03c4[samp], my_data)\n",
"\n",
" end\n",
"\n",
" return (out_\u03c3_\u03c0, out_\u03c3_\u03c4, out_\u03c4_T)\n",
"end\n",
"\n",
"\n",
"function block_tau(prior::Distribution, \u03c3_\u03c4, \u03c3_\u03c0, my_data)\n",
" block_lgs = LinGausSS(1., 1., \u03c3_\u03c4, \u03c3_\u03c0)\n",
" s0 = rand(prior)\n",
" p0 = prior.\u03c3\n",
" tau_hist = forward_backward_kalman_samp(1., 1., \u03c3_\u03c4, \u03c3_\u03c0, my_data, s0, p0)\n",
" return tau_hist\n",
"end\n",
"\n",
"\n",
"function block_sigtau(prior::Distribution, \u03c4_T, \u03c3_\u03c0::Float64)\n",
" (a, b) = prior.shape, prior.scale\n",
" T = length(\u03c4_T)\n",
" aprime = a + T/2.\n",
" eps_tau = Array(Float64, T)\n",
" eps_tau[2:end] = \u03c4_T[2:end] - \u03c4_T[1:end-1]\n",
" eps_tau[1] = 0.\n",
" bprime = b + dot(eps_tau, eps_tau)/2\n",
" return rand(InverseGamma(aprime, bprime))\n",
"end\n",
"\n",
"\n",
"function block_sigpi(prior::Distribution, \u03c4_T::Array{Float64, 1}, \u03c3_\u03c4, \u03c0_T::Array{Float64, 1})\n",
" (a, b) = prior.shape, prior.scale\n",
" T = length(\u03c4_T)\n",
" aprime = a + T/2.\n",
" eps_pi = \u03c0_T - \u03c4_T\n",
" bprime = b + dot(eps_pi, eps_pi)/2\n",
" return rand(InverseGamma(aprime, bprime))\n",
"end\n",
"\n",
"tic()\n",
"nsamp = 1000\n",
"(\u03c3_\u03c0, \u03c3_\u03c4, \u03c4_hist) = gibbsme(priors, infl, nsamp);\n",
"elapsed = toc();\n",
"\n",
"println(\"The sloppy version of Gibbs took $elapsed seconds to get $nsamp samples.\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"elapsed time: 0."
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"227804528 seconds\n",
"The sloppy version of Gibbs took 0.227804528 seconds to get 1000 samples.\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Open Source: Why it matters\n",
"\n",
">Everybody makes mistakes. And if you don't expose your raw data (here I would also add: your code), nobody will find your mistakes. -- Jean Claude Bradley\n",
"\n",
"## Some Benefits of Open Source Science\n",
"\n",
"* Encourages a value that should be at the core of science: REPRODUCIBILITY.\n",
"* Facilitates advances within the field by allowing others to see and use what has been done\n",
"* Code that is open source is accessible. Provides two big benefits:\n",
" - Seeing the code can be important in understanding how it works. If you aren't sure about exactly what an algorithm does then looking at the code can provide insights into what is happening.\n",
" - Having the code be accessible also allows you to make changes when needed and understand what the inputs and outputs of a function are. This removes the black box approach which is an appaling abuse of tools --It is wrong to \"use\" things that you don't understand at all.\n",
"* Open Source (under certain licenses...) can encourage participation from industry as well as academics"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Open Source: Use Git\n",
"\n",
"Git was initially created and used by Linus Torvalds to be a tool used in developing the Linux kernel. It has some very nice features that make it a powerful version control tool. It is often used in conjunction with a web-based hosting service.\n",
"\n",
"## Some Benefits of Git\n",
"* Non-Linear Development: Branches and Merging\n",
"* Distributed Development: Each developer has a local copy of the entire development history\n",
"* Efficient for Large Projects: Tests done by Mozilla have shown that it is an order of magnitude or faster than some other version controls and two orders of magnitude faster when reverting to old histories"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"source": [
"## Reproducibility\n",
"Obviously improving reproducibility helps limit bugs that are found in code (validating code). Example: The delta method vs Krinsky and Robb's estimator (Estimate the mean and variance of a function of a random variable).\n",
"\n",
">Most software today is very much like an Egyptian pyramid with millions of bricks piled on top of each other, with no structural integrity, but just done by brute force and thousands of slaves. --Alan Kay\n",
"\n",
"## Advancing Science\n",
"> Well, in the open source software (OSS) world, people genuinely build upon each other's work: we all know that citing an opaque paper that hides key details and doesn't include any code or data is not really building off it, it's simply preemptive action to ward off a nasty comment from a reviewer. --Fernando Perez\n",
"\n",
"## Incorporate Industry with Academics\n",
"http://nipy.sourceforge.net/nipy/stable/faq/johns_bsd_pitch.html\n",
"> Most software companies will not use GPL\u2019d code in their own software, even those that are highly committed to open source development, such as enthought, out of legitimate concern that use of the GPL will \u201cinfect\u201d their code base by its viral nature. --John Hunter\n",
"BSD > GPL"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# MCMC.jl\n",
"\n",
"This is a package within the Julia ecosystem that focuses on implementing relatively general algorithms for Markov Chain Monte Carlo methods. They currently don't have a Gibbs Sampler, so Spencer and I thought it would be worthwhile to try and fit our homework into their framework to provide them a Gibbs Sampler.\n",
"\n",
"> The Julia `MCMC` package provides a generic engine for implementing Bayesian statistical models using Markov Chain Monte\n",
"Carlo (MCMC) methods. While the package's framework aims at being extensible to accommodate user-specific models and\n",
"sampling algorithms, it ships with a wide selection of built-in MCMC samplers. It further offers output analysis and\n",
"MCMC diagnostic tools.\n",
"\n",
"There are three main components:\n",
"\n",
"1. The model: Contains the basic framework of a model. It should be able to evaluate the prior, likelihood, and posterior.\n",
"2. The sampler: This represents the MCMC algorithm. It is started from an initial parameter vector and uses a Julia task to repeatedly produce samples which are stored in a result structure.\n",
"3. The runner: The runner is used to \"run\" the algorithm along, including parameters like the number of samples, number of elements to burn in, thinning parameters, and objects that are needed between samples."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Set up to run things in parallel\n",
"typealias VectorOrOne{T} Union(Vector{T}, T)\n",
"\n",
"# Get rid of any excess processors\n",
"rmprocs(workers())\n",
"\n",
"# Add some new processors\n",
"addprocs(6)\n",
"nprocs()\n",
"\n",
"@everywhere begin\n",
" using Distributions\n",
" using MCMC\n",
" require(\"lingaussSS.jl\")\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/deriv_rules.jl:17.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:38.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:91.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a,b, ...}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass1.jl:107.\n",
"Use \"Any[a,b, ...]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b for (a,b) in c}\" at /home/chase/.julia/v0.4/ReverseDiffSource/src/pass2.jl:117.\n",
"Use \"Dict{Any,Any}([a=>b for (a,b) in c])\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:14.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:19.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:28.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/definitions/MCMCDerivRules.jl:32.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{}\" at /home/chase/.julia/v0.4/MCMC/src/parsers/expr_funcs.jl:86.\n",
"Use \"[]\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:76.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/ARS.jl:81.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:50.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/IMH.jl:54.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:62.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RWM.jl:66.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:64.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RAM.jl:68.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:107.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/MALA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:140.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMC.jl:146.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:111.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/HMCDA.jl:116.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/NUTS.jl:176.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:103.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/SMMALA.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:120.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/PMALA.jl:126.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:164.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/RMHMC.jl:168.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/samplers/Gibbs.jl:30.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SerialMC.jl:41.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n",
"\n",
"WARNING: deprecated syntax \"{a=>b, ...}\" at /home/chase/.julia/v0.4/MCMC/src/runners/SeqMC.jl:108.\n",
"Use \"Dict{Any,Any}(a=>b, ...)\" instead.\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\tau$ Block"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@everywhere function tau_block!(m::MCMCGibbsModel)\n",
" # Pull out prior for \u03c4_0. Get starting mean and covariance\n",
" dist = m.dists[:\u03c4_0]\n",
" \u03c4_0 = rand(dist)\n",
" P = dist.\u03c3\n",
"\n",
" # pull out current \u03c3_\u03c02 and current \u03c3_\u03c42 as well as data on \u03c0, T\n",
" \u03c3_\u03c02, \u03c3_\u03c42 = m.curr_params[:\u03c3_\u03c0], m.curr_params[:\u03c3_\u03c4]\n",
" \u03c0 = m.data[\"inflation\"]\n",
" T = m.data[\"T\"]\n",
" \n",
" \u03c4_sample = forward_backward_kalman_samp(1., sqrt(\u03c3_\u03c42), 1., sqrt(\u03c3_\u03c02), \u03c0, \u03c4_0, P^2)\n",
"\n",
" m.curr_params[:\u03c4_hist] = copy(\u03c4_sample)\n",
" nothing\n",
"end\n"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\sigma_\\tau$ Block"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@everywhere function sig_tau_block!(m::MCMCGibbsModel)\n",
" # Get the two Inv Gamma parameters\n",
" \u03c3_\u03c4_prior = m.dists[:\u03c3_\u03c4]\n",
" (a, b) = \u03c3_\u03c4_prior.shape, \u03c3_\u03c4_prior.scale\n",
"\n",
" # Get the useful parameters\n",
" \u03c4_0_prior = m.dists[:\u03c4_0]\n",
" \u03c4_hist = m.curr_params[:\u03c4_hist]\n",
" T = length(\u03c4_hist)\n",
" \u03b5_\u03c4 = zeros(\u03c4_hist)\n",
" \u03b5_\u03c4[2:end] = \u03c4_hist[2:end] - \u03c4_hist[1:end-1]\n",
" \u03b5_\u03c4[1] = \u03c4_hist[1] - rand(\u03c4_0_prior)\n",
"\n",
" # Draw from New Dist\n",
" aprime = a + T/2\n",
" bprime = b + dot(\u03b5_\u03c4, \u03b5_\u03c4)/2\n",
" \u03c3_\u03c4_prime = InverseGamma(aprime, bprime)\n",
"\n",
" m.curr_params[:\u03c3_\u03c4] = rand(\u03c3_\u03c4_prime)\n",
" nothing\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\sigma_\\pi$ Block"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@everywhere function sig_pi_block!(m::MCMCGibbsModel)\n",
" # Get the two Inv Gamma parameters\n",
" \u03c3_\u03c0_prior = m.dists[:\u03c3_\u03c0]\n",
" (a, b) = \u03c3_\u03c0_prior.shape, \u03c3_\u03c0_prior.scale\n",
"\n",
" # Get the useful parameters\n",
" \u03c4_hist = m.curr_params[:\u03c4_hist]\n",
" \u03c0_hist = m.data[\"inflation\"]\n",
" T = m.data[\"T\"]\n",
" \u03b5_\u03c0 = \u03c4_hist - \u03c0_hist\n",
"\n",
" # Draw from New Dist\n",
" aprime = a + T/2\n",
" bprime = b + dot(\u03b5_\u03c0, \u03b5_\u03c0)/2\n",
" \u03c3_\u03c0_prime = InverseGamma(aprime, bprime)\n",
"\n",
" m.curr_params[:\u03c3_\u03c0] = rand(\u03c3_\u03c0_prime)\n",
" nothing\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Create the Model"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"function prepare_model(nchains::Int=1)\n",
" # Get the data\n",
" infl = float64(readcsv(\"inflation_data.csv\")[:, 2])\n",
" data = Dict()\n",
" data[\"T\"] = length(infl)\n",
" data[\"inflation\"] = infl\n",
"\n",
" # Priors\n",
" \u03c3_\u03c0_prior = InverseGamma(2., 2.)\n",
" \u03c3_\u03c4_prior = InverseGamma(2., 2.)\n",
" \u03c4_0_prior = Normal(0., 1.)\n",
" \u03b8_priors = Dict{Symbol, Distribution}()\n",
" \u03b8_priors[:\u03c3_\u03c0] = \u03c3_\u03c0_prior\n",
" \u03b8_priors[:\u03c3_\u03c4] = \u03c3_\u03c4_prior\n",
" \u03b8_priors[:\u03c4_0] = \u03c4_0_prior\n",
"\n",
" # Block Symbol to Number\n",
" blocksym2num = Dict{Symbol, Int}()\n",
" blocksym2num[:\u03c4_his] = 1\n",
" blocksym2num[:\u03c3_\u03c4] = 2\n",
" blocksym2num[:\u03c3_\u03c0] = 3\n",
"\n",
" # Number of Blocks\n",
" n_blocks = 3\n",
" \n",
" block_funcs = Dict{Int, Function}()\n",
" block_funcs[1] = tau_block!\n",
" block_funcs[2] = sig_tau_block!\n",
" block_funcs[3] = sig_pi_block!\n",
" \n",
" out = Array(MCMCGibbsModel, nchains)\n",
" \n",
" for i=1:nchains\n",
" # Initial parameters --Need one for each chain\n",
" curr_\u03b8 = Dict{Symbol, VectorOrOne{Float64}}()\n",
" curr_\u03b8[:\u03c3_\u03c0] = rand(\u03c3_\u03c0_prior)\n",
" curr_\u03b8[:\u03c3_\u03c4] = rand(\u03c3_\u03c4_prior)\n",
" curr_\u03b8[:\u03c4_hist] = randn(data[\"T\"])\n",
" \n",
" out[i] = MCMCGibbsModel(curr_\u03b8, \u03b8_priors, blocksym2num,\n",
" block_funcs, data, n_blocks)\n",
" end\n",
" return out\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 12,
"text": [
"prepare_model (generic function with 2 methods)"
]
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Create and Run the tasks\n",
"\n",
"We will be running 6 chains that will take 10,000,000 draws. I will use the first 50,000 as burn-in and some people recommend \"thinning\" your draws from the Gibbs sampler so I will only use every 100th draw."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"nchains = nprocs() - 1\n",
"\n",
"# Sampling parameters\n",
"burnin = 500\n",
"thin = 1\n",
"endsamp = 10000\n",
"burnthinend = burnin:thin:endsamp\n",
"n_samples = size(burnthinend, 1)\n",
"\n",
"if myid() == 1\n",
" mod = prepare_model(nchains)\n",
" ser_gibbs = SerialGibbs(burnthinend)\n",
" tsk = mod*Gibbs()*ser_gibbs\n",
" chains = prun(tsk)\n",
"end\n",
"\n",
"display(chains)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"6-element Array{Any,1}:\n",
" 3 parameters, 9501 samples (per parameter) 1.4 sec.\n",
" 3 parameters, 9501 samples (per parameter) 1.1 sec.\n",
" 3 parameters, 9501 samples (per parameter) 1.5 sec.\n",
" 3 parameters, 9501 samples (per parameter) 1.4 sec.\n",
" 3 parameters, 9501 samples (per parameter) 1.6 sec.\n",
" 3 parameters, 9501 samples (per parameter) 1.4 sec."
]
}
],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"using PyCall\n",
"using PyPlot\n",
"using KernelDensity"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"outputs": [],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@pyimport seaborn"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Plott\n",
"n_violinplots = 10 ;"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mod[1].dists"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 23,
"text": [
"Dict{Symbol,Distribution{F<:VariateForm,S<:ValueSupport}} with 3 entries:\n",
" :\u03c3_\u2026 => InverseGamma( shape=2.0 scale=2.0 )\n",
" :\u03c3_\u2026 => InverseGamma( shape=2.0 scale=2.0 )\n",
" :\u03c4_0 => Normal( \u03bc=0.0 \u03c3=1.0 )"
]
}
],
"prompt_number": 23
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Displaying Priors\n",
"\n",
"I chose the following priors (although I had no real theoretical foundation for them).\n",
"\n",
"* $\\sigma_\\pi$: InverseGamma(2, 2)\n",
"* $\\sigma_\\tau$: InverseGamma(2, 2)\n",
"* $\\tau_0$: Normal(0, 1)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pfig, pax = subplots(2, 2)\n",
"pax[:] = pax[:]\n",
"\n",
"psigpi = rand(mod[1].dists[:\u03c3_\u03c0], 10000)\n",
"psigtau = rand(mod[1].dists[:\u03c3_\u03c4], 10000)\n",
"ptau0 = rand(mod[1].dists[:\u03c4_0], 1000000)\n",
"\n",
"psigpi_kde = kde(psigpi)\n",
"psigtau_kde = kde(psigtau)\n",
"ptau0_kde = kde(ptau0)\n",
"\n",
"pax[1][:plot](psigpi_kde.x, psigpi_kde.density)\n",
"pax[1][:set_title](L\"The Prior for $\\sigma_\\pi$\")\n",
"pax[1][:set_xlim]([0, 10])\n",
"\n",
"pax[2][:plot](psigtau_kde.x, psigtau_kde.density)\n",
"pax[2][:set_title](L\"The Prior for $\\sigma_\\tau$\")\n",
"pax[2][:set_xlim]([0, 10])\n",
"\n",
"pax[3][:plot](ptau0_kde.x, ptau0_kde.density)\n",
"pax[3][:set_title](L\"The Prior for $\\tau_0$\")\n",
"\n",
"tight_layout()"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d4a4eb940>)"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Displaying Results: $\\sigma_\\pi$\n",
"\n",
"Notice the scale on the x-axis compared to the x-axis on the prior previously shown. It tightened down to a small range even though the prior was relatively diffuse."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg_sigpi, ax_sigpi = subplots(1, 1)\n",
"\n",
"for chain=1:nchains\n",
" theData = squeeze(chains[chain].samples[:\u03c3_\u03c0], 1)\n",
" theKernel = kde(theData)\n",
" ax_sigpi[:plot](theKernel.x, theKernel.density, alpha=.75, label=\"Chain $chain\")\n",
" ax_sigpi[:set_xlabel](L\"$\\sigma_\\pi$\")\n",
"end\n",
"\n",
"plot_title = latexstring(\"The Kernel Density of \\$\\\\sigma_\\\\pi\\$\")\n",
"ax_sigpi[:set_title](plot_title)\n",
"fulldata_\u03c3_\u03c0 = [squeeze(chains[i].samples[:\u03c3_\u03c0], 1) for i in nchains][1]\n",
"fullkde_\u03c3_\u03c0 = kde(fulldata_\u03c3_\u03c0)\n",
"ax_sigpi[:plot](fullkde_\u03c3_\u03c0.x, fullkde_\u03c3_\u03c0.density, linestyle=\":\",\n",
" linewidth=2, alpha=1, color=\"k\", label=\"Combined Chains\")\n",
"\n",
"ax_sigpi[:legend]()\n",
"\n",
"tight_layout()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3a7f9e80>)"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Displaying Results: $\\sigma_\\tau$\n",
"\n",
"Once again, notice how much the prior tightened in this case as well."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg_sigtau, ax_sigtau = subplots(1, 1)\n",
"\n",
"for chain=1:nchains\n",
" theData = squeeze(chains[chain].samples[:\u03c3_\u03c4], 1)\n",
" theKernel = kde(theData)\n",
" ax_sigtau[:plot](theKernel.x, theKernel.density, alpha=.75, label=\"Chain $chain\")\n",
"end\n",
"\n",
"plot_title = latexstring(\"The Kernel Density of \\$\\\\sigma_\\\\tau\\$\")\n",
"ax_sigtau[:set_title](plot_title)\n",
"fulldata_\u03c3_\u03c4 = [squeeze(chains[i].samples[:\u03c3_\u03c4], 1) for i in nchains][1]\n",
"fullkde_\u03c3_\u03c4 = kde(fulldata_\u03c3_\u03c4)\n",
"ax_sigtau[:plot](fullkde_\u03c3_\u03c4.x, fullkde_\u03c3_\u03c4.density, linestyle=\":\",\n",
" linewidth=2, alpha=1, color=\"k\", label=\"Combined Chains\")\n",
"\n",
"ax_sigtau[:legend]()\n",
"\n",
"tight_layout()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3a7cac18>)"
]
}
],
"prompt_number": 32
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Displaying Results: $\\tau^T$\n",
"\n",
"Here I make use of violin plots to show the distribution of the history of $\\tau^T$. It is technically a random variable of dimension $T$, but here I use a path of distributions to demonstrate it. I have 6 chains of 10000 draws of histories $\\tau^T$. The violin plots show the density across possible values of $\\tau_t$ (by how thick the violin plot is) at time $t$ (which is shown on the x-axis). I also plotted the history of inflation values. It is interesting to note that the violin plots seem to move to match the history of inflation which is what we expect to happen."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg_tauhist, ax_tauhist = subplots(1, 1)\n",
"n_vplots = 10\n",
"\n",
"for chain=1:nchains\n",
" theData = chains[chain].samples[:\u03c4_hist]'\n",
" ndraws, T = size(theData)\n",
" stepsize = iceil(T/n_vplots)\n",
" seaborn.violinplot(theData[:, 1:stepsize:T], names=[1:stepsize:T],\n",
" axes=ax_tauhist, alpha=.15)\n",
" ax_tauhist[:set_title](L\"Violin Plots of Density of $\\tau^T$\")\n",
" ax_tauhist[:set_xlabel](L\"$T$\")\n",
"end\n",
"\n",
"infl = float64(readcsv(\"inflation_data.csv\")[:, 2])\n",
"inflx = linspace(1, n_vplots, 275)\n",
"ax_tauhist[:plot](inflx, infl, color=\"g\", alpha=.375, label=\"inflation\")\n",
"ax_tauhist[:legend]()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3a699048>)"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 33,
"text": [
"PyObject <matplotlib.legend.Legend object at 0x7f1d3a207908>"
]
}
],
"prompt_number": 33
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Thinking about Convergence"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"n_chainplots = 4 ;\n",
"n_samples = size(chains[1].range, 1)\n",
"chainplots_uptostep = ifloor([.025, .1, .4, 1.] .* n_samples)"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 36,
"text": [
"4-element Array{Int64,1}:\n",
" 237\n",
" 950\n",
" 3800\n",
" 9501"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\sigma_\\pi$\n",
"\n",
"We see that as we take more draws, the samples are converging to the black dotted line which is the distribution of all draws taken across chains."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg_sigpi, ax_sigpi = subplots(2, 2)\n",
"ax_sigpi[:] = ax_sigpi[:]\n",
"\n",
"\n",
"for uptosample=1:n_chainplots\n",
" curr_uptosample = chainplots_uptostep[uptosample]\n",
" for chain=1:nchains\n",
" theData = squeeze(chains[chain].samples[:\u03c3_\u03c0], 1)\n",
" theKernel = kde(theData[1:curr_uptosample])\n",
" ax_sigpi[uptosample][:plot](theKernel.x, theKernel.density, alpha=.75)\n",
" end\n",
" plot_title = latexstring(\"The Kernel Density of \\$\\\\sigma_\\\\pi\\$ with $curr_uptosample draws\")\n",
" ax_sigpi[uptosample][:set_title](plot_title)\n",
" ax_sigpi[uptosample][:set_xlabel](L\"$\\sigma_\\pi$\")\n",
" ax_sigpi[uptosample][:set_yticks]([])\n",
" ax_sigpi[uptosample][:plot](fullkde_\u03c3_\u03c0.x, fullkde_\u03c3_\u03c0.density, linestyle=\":\",\n",
" linewidth=2, alpha=1, color=\"k\", label=\"Combined Chains\")\n",
"end\n",
"\n",
"tight_layout()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3a5776d8>)"
]
}
],
"prompt_number": 37
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\sigma_\\tau$\n",
"\n",
"We see that as we take more draws, the samples are converging to the black dotted line which is the distribution of all draws taken across chains."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg_sigtau, ax_sigtau = subplots(2, 2)\n",
"ax_sigtau[:] = ax_sigtau[:]\n",
"\n",
"for uptosample=1:n_chainplots\n",
" curr_uptosample = chainplots_uptostep[uptosample]\n",
" for chain=1:nchains\n",
" theData = squeeze(chains[chain].samples[:\u03c3_\u03c4], 1)\n",
" theKernel = kde(theData[1:curr_uptosample])\n",
" ax_sigtau[uptosample][:plot](theKernel.x, theKernel.density, alpha=.75)\n",
" end\n",
" plot_title = latexstring(\"The Kernel Density of \\$\\\\sigma_\\\\tau\\$ with $curr_uptosample draws\")\n",
" ax_sigtau[uptosample][:set_title](plot_title)\n",
" ax_sigtau[uptosample][:set_xlabel](L\"$\\sigma_\\tau$\")\n",
" ax_sigtau[uptosample][:set_yticks]([])\n",
" ax_sigtau[uptosample][:set_xlim]([0., 0.05])\n",
" \n",
" ax_sigtau[uptosample][:plot](fullkde_\u03c3_\u03c4.x, fullkde_\u03c3_\u03c4.density, linestyle=\":\",\n",
" linewidth=2, alpha=1, color=\"k\", label=\"Combined Chains\")\n",
"end\n",
"\n",
"tight_layout()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3bc02588>)"
]
}
],
"prompt_number": 38
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# $\\tau^T$\n",
"\n",
"These plots were hard to see on a single set of sub-axes, so I made the plots (which are similar to the last ones) separate boxes and they are increasing in number of draws. The first only includes first 237 draws, the second includes first 950 draws etc... See plots following this slide."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig_tauT, ax_tauT = subplots()\n",
"\n",
"curr_uptosample = chainplots_uptostep[1]\n",
"theData = chains[1].samples[:\u03c4_hist]'\n",
"\n",
"ndraws, T = size(theData)\n",
"stepsize = iceil(T/n_vplots)\n",
"\n",
"seaborn.violinplot(theData[1:curr_uptosample, 1:stepsize:T], \n",
" names=[1:stepsize:T], \n",
" alpha=.15)\n",
"\n",
"ax_tauT[:set_title](L\"Violin Plots of Density of $\\tau^T$\")\n",
"ax_tauT[:set_xlabel](L\"$T$\")\n",
"plot_title = latexstring(\"The Violin Plot of \\$\\\\tau_0\\$ with $curr_uptosample draws\")\n",
"ax_tauT[:set_title](plot_title)\n",
"ax_tauT[:set_xlabel](L\"$t$\")\n",
"ax_tauT[:set_yticks]([])\n",
"\n",
"show()"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d39128b70>)"
]
}
],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig_tauT, ax_tauT = subplots()\n",
"\n",
"curr_uptosample = chainplots_uptostep[2]\n",
"theData = chains[1].samples[:\u03c4_hist]'\n",
"\n",
"ndraws, T = size(theData)\n",
"stepsize = iceil(T/n_vplots)\n",
"\n",
"seaborn.violinplot(theData[1:curr_uptosample, 1:stepsize:T], \n",
" names=[1:stepsize:T], \n",
" alpha=.15)\n",
"\n",
"ax_tauT[:set_title](L\"Violin Plots of Density of $\\tau^T$\")\n",
"ax_tauT[:set_xlabel](L\"$T$\")\n",
"plot_title = latexstring(\"The Violin Plot of \\$\\\\tau_0\\$ with $curr_uptosample draws\")\n",
"ax_tauT[:set_title](plot_title)\n",
"ax_tauT[:set_xlabel](L\"$t$\")\n",
"ax_tauT[:set_yticks]([])\n",
"\n",
"show()"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d39ae0be0>)"
]
}
],
"prompt_number": 48
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig_tauT, ax_tauT = subplots()\n",
"\n",
"curr_uptosample = chainplots_uptostep[3]\n",
"theData = chains[1].samples[:\u03c4_hist]'\n",
"\n",
"ndraws, T = size(theData)\n",
"stepsize = iceil(T/n_vplots)\n",
"\n",
"seaborn.violinplot(theData[1:curr_uptosample, 1:stepsize:T], \n",
" names=[1:stepsize:T], \n",
" alpha=.15)\n",
"\n",
"ax_tauT[:set_title](L\"Violin Plots of Density of $\\tau^T$\")\n",
"ax_tauT[:set_xlabel](L\"$T$\")\n",
"plot_title = latexstring(\"The Violin Plot of \\$\\\\tau_0\\$ with $curr_uptosample draws\")\n",
"ax_tauT[:set_title](plot_title)\n",
"ax_tauT[:set_xlabel](L\"$t$\")\n",
"ax_tauT[:set_yticks]([])\n",
"\n",
"show()"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d3942df60>)"
]
}
],
"prompt_number": 49
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig_tauT, ax_tauT = subplots()\n",
"\n",
"curr_uptosample = chainplots_uptostep[4]\n",
"theData = chains[1].samples[:\u03c4_hist]'\n",
"\n",
"ndraws, T = size(theData)\n",
"stepsize = iceil(T/n_vplots)\n",
"\n",
"seaborn.violinplot(theData[1:curr_uptosample, 1:stepsize:T], \n",
" names=[1:stepsize:T], \n",
" alpha=.15)\n",
"\n",
"ax_tauT[:set_title](L\"Violin Plots of Density of $\\tau^T$\")\n",
"ax_tauT[:set_xlabel](L\"$T$\")\n",
"plot_title = latexstring(\"The Violin Plot of \\$\\\\tau_0\\$ with $curr_uptosample draws\")\n",
"ax_tauT[:set_title](plot_title)\n",
"ax_tauT[:set_xlabel](L\"$t$\")\n",
"ax_tauT[:set_yticks]([])\n",
"\n",
"show()"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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",
"text": [
"Figure(PyObject <matplotlib.figure.Figure object at 0x7f1d39d831d0>)"
]
}
],
"prompt_number": 50
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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