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Computing2-2.pdf (46363, 2019-10-14)
sample-data (0, 2019-10-14)
sample-data\full-dataset.csv (177405, 2019-10-14)
sample-data\gibbs.cu (11138, 2019-10-14)
sample-data\prepared-data.csv (44081, 2019-10-14)

# Gibbs Sampler Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution, when direct sampling is difficult. This sequence can be used to approximate the joint distribution (e.g., to generate a histogram of the distribution); to approximate the marginal distribution of one of the variables, or some subset of the variables. This program implements a MCMC algorithm for the following hierarchical model: y_k ~ Poisson(n_k * theta_k) theta_k ~ Gamma(a, b) a ~ Unif(0, a0) b ~ Unif(0, b0) I let a0 and b0 be arbitrarily large. Arguments: 1) input file name With two space delimited columns holding integer values for y and float values for n. 2) number of trials (1000 by default) Output: A comma delimited file containing a column for a, b, and each theta. All output is written to standard out.

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