Bayesian Inference with Inla - Virgilio Gomez-Rubio
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The Integrated Nested Laplace Approximation (INLA) is a popular method for approximate Bayesian inference. This book provides an introduction to the underlying INLA methodology and practical guidance on how to fit different models with R-INLA and R. This covers a wide range of applications, such as multilevel models, spatial models and survival models, The book will also cover recent research on how to exte ... Full description
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Description
The Integrated Nested Laplace Approximation (INLA) is a popular method for approximate Bayesian inference. This book provides an introduction to the underlying INLA methodology and practical guidance on how to fit different models with R-INLA and R. This covers a wide range of applications, such as multilevel models, spatial models and survival models, The book will also cover recent research on how to extend the types of models that can be fitted with INLA and R-INLA. This will include built-in features in R-INLA to define new latent models directly in R as well as combining INLA with numerical integration and MCMC methods.
More Information
| Author | Virgilio Gomez-Rubio |
|---|---|
| Publisher | Taylor & Francis Ltd |
| Release year | 2020 |
| Cover type | Hardcover |
| EAN | 9781138039872 |