Discrete Bayes with R

Discrete Bayes with R

C*-algebras on r-discrete Abelian Groupoids

We study certain function algebras and their operator algebra completions on r-discrete abelian groupoids, the corresponding conditional expectations, maximal abelian subalgebras (masa) and eigen-functionals. We give a semidirect product decomposition for an abelian groupoid. This is done through a matched pair and leads to a C*-diagonal (for a special case). We use this decomposition to study ...

EbayesThresh: R Programs for Empirical Bayes Thresholding

Suppose that a sequence of unknown parameters is observed subject to independent Gaussian noise. The EbayesThresh package in the S language implements a class of Empirical Bayes thresholding methods that can take advantage of possible sparsity in the sequence, to improve the quality of estimation. The prior for each parameter in the sequence is a mixture of an atom of probability at zero and a ...

Teaching Inference Using Bayes and Discrete Models

Teaching classical statistical inference at an elementary level can be hard, due to the diiculty in teaching sampling distributions and the correct interpretation of statistical conndence. Bayesian methods have the attractive feature that statistical conclusions can be stated using the language of subjective probability. Simple methods of teaching Bayes rule are described and these methods are ...

Discrete Time Markov Chains with R by

The markovchain package aims to provide S4 classes and methods to easily handle Discrete Time Markov Chains (DTMCs), filling the gap with what is currently available in the CRAN repository. In this work, I provide an exhaustive description of the main functions included in the package, as well as hands-on examples. Introduction DTMCs are a notable class of stochastic processes. Although their b...