Articles by Nathan VanHoudnos

Post 10: Multicore parallelism in MCMC

September 24, 2014 | Nathan VanHoudnos

MCMC is by its very nature a serial algorithm -- each iteration depends on the results of the last iteration. It is, therefore, rather difficult to parallelize MCMC code so that a single chain will run more quickly by splitting … Continue reading → [Read more...]

Post 9: Tuning the complete sampler

October 25, 2013 | Nathan VanHoudnos

This post demonstrates how to tune the sampler for optimal acceptance probabilities and demonstrates that the whole sampler works. Tuning the complete sampler for acceptance rate Tuning the sampler's acceptance rates consists of running the sampler several times while tweaking … Continue reading → [Read more...]

Post 2: Generating fake data

October 6, 2013 | Nathan VanHoudnos

In order to check that an estimation algorithm is working properly, it is useful to see if the algorithm can recover the true parameter values in one or more simulated "test" data sets. This post explains how to build such … Continue reading → [Read more...]

Post 1: A Bayesian 2PL IRT model

October 4, 2013 | Nathan VanHoudnos

In this post, we define the Two-Parameter Logistic (2PL) IRT model, derive the complete conditionals that will form the basis of the sampler, and discuss our choice of prior specification. We can find the appropriate values of numerically in R … Continue reading → [Read more...]

Post 0: Getting Started with R

October 4, 2013 | Nathan VanHoudnos

R is an interpreted programming language that makes it easy to think about statistics instead of thinking about programming. Unlike other programming languages, R is commonly used by typing commands one-at-a-time in an interactive session. RStudio is a program that … Continue reading → [Read more...]

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