Bayesian Regression Modeling with Inla - Xiaofeng Wang,Julian J Faraway,Yu Yue Ryan
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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) algorit ... Full description
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Description
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.
More Information
| Author | Xiaofeng Wang, Julian J Faraway, Yu Yue Ryan |
|---|---|
| Publisher | CRC Press |
| Release year | 2018 |
| Cover type | Hardcover |
| EAN | 9781498727259 |