期刊
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷 84, 期 3, 页码 513-525出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949655.2012.717292
关键词
double generalized linear models; stochastic models; Bayesian methodology; biparametric exponential family
资金
- Research Division of the National University of Colombia (Universidad Nacional de Colombia)
- CNPq-Brazil
- CAPES-Brazil
In this paper, we develop a new class of double generalized linear models, introducing a random-effect component in the link function describing the linear predictor related to the precision parameter. This is a useful procedure to take into account extra variability and also to make the model more robust. The Bayesian paradigm is adopted to make inference in this class of models. Samples of the joint posterior distribution are drawn using standard Monte Carlo Markov Chain procedures. Finally, we illustrate this algorithm by considering simulated and real data sets.
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