Dec 29, 2017 · This framework provides new perspectives on some established GLM algorithms derived from SLM ones and also suggests novel extensions for some ...
Abstract—In this letter, we present a unified Bayesian inference framework for generalized linear models (GLM), which iteratively reduces the GLM problem to ...
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Dec 29, 2017 · Abstract—In this letter, we present a unified Bayesian inference framework for generalized linear models (GLM) which iteratively.
A unified Bayesian inference framework for generalized linear models (GLM), which iteratively reduces the GLM problem to a sequence of standard linear model ...
Abstract. The recent work `A unified Bayesian inference framework for generalized linear models' \cite{meng1} shows that the GLM can be solved via iterating ...
In this course, we will introduce GLMs as a unified, coherent, and easily extendable framework for the analysis of many types of data, including Normal ( ...
Full article: Bayesian inference for generalized linear mixed models
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In this paper, we conduct an extensive simulation study to evaluate the performance of INLA for estimation of the hierarchical Poisson regression models with ...
We propose to use a generalized truncated multivariate normal distribution (TMVN) prior (Li and Ghosh, 2015) which leads to an efficient Gibbs sampling method ...
The proposed product slice sampler is shown to be uniformly ergodic, having a geometric convergence rate under a set of mild regularity conditions satisfied by ...
This paper provides a unified approach to both Bayes high dimensional statistics and Bayes nonparametrics in a general framework of structured linear models.
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