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Bayesian Regression Modeling with INLA
ISBN-13:
9781351165747
Veröffentl:
2018
Seiten:
324
Autor:
Xiaofeng Wang
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
2 - DRM Adobe
Sprache:
Englisch
Beschreibung:
This book addresses the applications of extensively used regression models under a Bayesian framework. It emphasizes efficient Bayesian inference through integrated nested Laplace approximations (INLA) and real data analysis using R. The INLA method directly computes very accurate approximations to the posterior marginal distributions and is a promising alternative to Markov chain Monte Carlo (MCMC) algorithms, which come with a range of issues that impede practical use of Bayesian models.
Introduction to Bayesian Statistics. Bayesian Hierarchical Modeling. Model-Based Bayesian Inference. Linear and Generalized Linear Models. Linear and Generalized Linear Mixed Models. Zero-Inflated Mixture Models. Survival Analysis. Nonparametric Regression and Additive Models. Functional Regression Models. Measurement Error Models. Quantile Regression.
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