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library('doParallel') | |
registerDoParallel(cores = 4) | |
#' Spike-and-Slab Regression using Gibbs Sampling for p > 1 predictors | |
#' | |
#' @param y: vector of responses | |
#' @param X: matrix of predictor values | |
#' @param nr_samples: indicates number of samples drawn | |
#' @param a1: parameter a1 of Gamma prior on variance sigma2e |
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# devtools::install_github("dkahle/dirichlet") | |
library('TeX') | |
library('ggplot2') | |
library('gridExtra') | |
library('dirichlet') | |
plot_dirichlet <- function(alphas = c(.5, .5, .5), add_points = FALSE) { | |
f <- function(v) ddirichlet(v, alphas) | |
mesh <- simplex_mesh(.0025) %>% as.data.frame %>% tbl_df |
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bfx <- function(x, tstat, n, mu, gamma, k, v = n - 2) { | |
num <- integrate(function(delta) { | |
dt(tstat, df = v, ncp = sqrt(n)*delta)/gamma * dnorm((delta - mu)/gamma) | |
}, -Inf, Inf)$value | |
dt(tstat, df = v, ncp = sqrt(n)*x) / num | |
} | |
lo <- uniroot(function(x) bfx(x, .5, 10, 0, .3) - 1, interval = c(-1, 0))$root |
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# for https://www.facebook.com/efpsa.jeps/posts/1278843852167100 | |
library('ggplot2') | |
library('gridExtra') | |
set.seed(1774) | |
# generate data | |
A = c(rnorm(20, 20, 4), rnorm(20, 40, 4)) # mixture distribution | |
B = rt(30, 1) + 30 # from a heavy-tailed distribution (Cauchy) | |
C = c(25, 35, 33) # just three data points |
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--- | |
title: "Bayesian effect size for ANOVA designs" | |
author: "Fabian Dablander, Maarten Marsman" | |
date: "May 22, 2016" | |
output: html_document | |
--- | |
## 1) Example: One-way design | |
Download the data from [https://osf.io/zcipy/](https://osf.io/zcipy/), save it under | |
"example1.sav" in the current directory. |
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function PCA(X) | |
## Y = PX | |
# required: | |
#- P such that | |
#- we get rid of 2nd order correlation, Cov(Y) = D [some diagonal matrix] | |
# method: | |
#- project onto an orthogonal space spanned by the | |
#- eigenvectors with variances equal to the eigenvalues |
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library('rvest') | |
library('stringr') | |
fachschaft = 'http://wiki.psyfako.org/index.php?title=Liste_der_Psychologie_Fachschaften' | |
emails = read_html(fachschaft) %>% | |
html_nodes('p, a, span') %>% html_text(.) %>% | |
str_replace('\\[at\\]', '@') %>% str_replace('\\(at\\)', '@') %>% | |
str_replace('\\[ät\\]', '@') %>% str_replace('\\[dot\\]', '.') %>% |
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shinyApp( | |
options = list(width = '25%', height = '25%'), | |
ui = shinyUI(fluidPage( | |
sidebarLayout( | |
sidebarPanel( | |
sliderInput('e', label = 'e', min = 0, max = 100, value = 10, step = 1), | |
sliderInput('N', label = 'N', min = 10, max = 500, value = 100, step = 1), | |
numericInput('seed', label = 'random seed', value = 1774), | |
numericInput('lambda', label = 'penalty (lambda)', value = 0), | |
textInput('true', label = 'true function f(x)', value = 'x^2'), |
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library('runjags') | |
lasso.bayes <- function(y, X, n.iter = 10000) { | |
ms <- ' | |
model { | |
sigma ~ dunif(0, 100) | |
tau <- pow(sigma, -2) | |
lambda ~ dunif(0, 10) |
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# c('practicality', 'difficulty', 'some color, dunno') | |
papers <- rbind( | |
# paper we discuss | |
c(5, 3, 1), # Lindley (1993) | |
c(8, 0, 1), # Kruschke (2010) | |
c(4, 3, 1), # Wagenmakers (2007) | |
c(5, 2, 1), # Dienes (2011) | |
c(3, 7, 1), # Vandekerckhove, Matzke, Wagenmakers (2015) | |
c(4, 8, 1), # Rouder & Morey (2012) |
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