ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models
Dublin Core
Title
ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models
Subject
: BMA, GLM, RJMCMC, parallelization, gretl
Description
This paper describes the gretl function package ParMA, which provides Bayesian
model averaging (BMA) in generalized linear models. In order to overcome the lack
of analytical specification for many of the models covered, the package features an implementation of the reversible jump Markov chain Monte Carlo technique, following the
original idea by Green (1995), as a flexible tool to model several specifications. Particular
attention is devoted to computational aspects such as the automatization of the model
building procedure and the parallelization of the sampling scheme.
model averaging (BMA) in generalized linear models. In order to overcome the lack
of analytical specification for many of the models covered, the package features an implementation of the reversible jump Markov chain Monte Carlo technique, following the
original idea by Green (1995), as a flexible tool to model several specifications. Particular
attention is devoted to computational aspects such as the automatization of the model
building procedure and the parallelization of the sampling scheme.
Creator
Riccardo (Jack) Lucchetti
Source
https://www.jstatsoft.org/article/view/v104i02
Publisher
Università Politecnica delle Marche
Date
September 2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Riccardo (Jack) Lucchetti, “ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models,” Repository Horizon University Indonesia, accessed April 5, 2025, https://repository.horizon.ac.id/items/show/8272.