Inference with gamma and inverse gamma prior densities in left-censored regression
Abstract
Left-censored linear regression models are quite popular models and have been deeply considered in the last three decades. In this paper, we consider a completely Bayesian approach for making a new Markov chain Monte Carlo (MCMC) algorithm with tractable full posteriors. Simulated consequences and real data analyses depict that the new Markov chain Monte Carlo algorithm has excellent mixing property and carry out very well than the present methods based on prediction accuracy.
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PDFDOI: http://dx.doi.org/10.21533/pen.v9i1.1776
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Copyright (c) 2021 Esmaeel Ali Alselmawi, Rahim Alhamzawi
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This work is licensed under a Creative Commons Attribution 4.0 International License.
ISSN: 2303-4521
Digital Object Identifier DOI: 10.21533/pen
This work is licensed under a Creative Commons Attribution 4.0 International License