ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models

Autor: Riccardo (Jack) Lucchetti, Luca Pedini
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Statistical Software, Vol 104, Pp 1-39 (2022)
Druh dokumentu: article
ISSN: 1548-7660
DOI: 10.18637/jss.v104.i02
Popis: 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.
Databáze: Directory of Open Access Journals