2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.CO2016
The Bayesian analysis of contingency table data using the bayesloglin R package
Matthew Friedlander
For log-linear analysis, the hyper Dirichlet conjugate prior is available to work in the Bayesian paradigm. With this prior, the MC3 algorithm allows for exploration of the space o…
stat.CO2016★ 2 cited
Fitting log-linear models in sparse contingency tables using the eMLEloglin R package
Matthew Friedlander
Log-linear modeling is a popular method for the analysis of contingency table data. When the table is sparse, and the data falls on a proper face of the convex support, there a…
stat.CO2016
Analyzing Genome-wide Association Study Data with the R Package genMOSS
Matthew Friedlander, Adrian Dobra, Helene Massam +1
The R package (R Core Team (2016)) genMOSS is specifically designed for the Bayesian analysis of genome-wide association study data. The package implements the mode oriented stocha…