trappmartin

#!/bin/bash
#######################################################
# EXPORTS
#######################################################

# Expand the history size
export HISTFILESIZE=10000
export HISTSIZE=500

# Set the default editor

trappmartin

set nocompatible
color pablo
syntax on
set number
set backspace=indent,eol,start

" highlight found words
set hlsearch

" show matching parenthesis

trappmartin

%s/\({.*}\)\(([^)]*)\)\(\s=\)/\2 where \1\3/g

trappmartin

using Turing, Turing.RandomMeasures

@model dpmixture(x) = begin
    rpm = DirichletProcess(1.0)
    n = zeros(Int, length(x))
    z = zeros(Int, length(x))
    
    for i in eachindex(x)
        z[i] ~ ChineseRestaurantProcess(rpm, n)
        n[z[i]] += 1

trappmartin

using Turing
using Optim
using UnicodePlots
import StatsBase.mode

@model gdemo_d() = begin
  s ~ InverseGamma(2, 3)
  m ~ Normal(0, sqrt(s))
  1.5 ~ Normal(m, sqrt(s))
  2.0 ~ Normal(m, sqrt(s))

trappmartin

using DrWatson
@quickactivate "DynamicPPL_NeurIPS"

using Turing
using LinearAlgebra
using Random: seed!
seed!(1)

@model testmodel(p, O) = begin
    x ~ Categorical(p)

trappmartin

using Turing
using Bijectors
using LinearAlgebra

Bijectors.bijector(d::LKJ) = PDBijector()

@model function correlation(y)
    N,D = size(y)
    
    mu ~ filldist(truncated(Normal(0, 100), -10, 10), D)

trappmartin

using Turing

@model function ibp(y, α, kmax, ::Type{MV}=Vector{Float64}) where {MV}
   N = length(y)
   
   ks = tzeros(Int, N)
   ks[1] ~ Poisson(α)
   ks[1] = ks[1] <= kmax ? ks[1] : kmax
   
   z = tzeros(Int, N, kmax)

trappmartin

using Turing

# This is a crappy implementation of Isabel's model.
# For simplicity, I assume all data to be positiv-real valued.
# Isabel's paper: http://proceedings.mlr.press/v70/valera17a/valera17a.pdf

@model function adst(y, ::Type{TV}=Vector{Float64}) where {TV}
  
  N,D = size(y)
  

trappmartin

using Turing
using Turing.RandomMeasures

# Implementation of infinite mixture model
@model function imm(y, α, ::Type{T}=Vector{Float64}) where {T}
    N = length(y)
    nk = tzeros(Int, N)
    z = tzeros(Int, N)

    for i in 1:N