{"product_id":"bayesian-regression-modeling-with-inla-1","title":"Bayesian Regression Modeling with INLA","description":"\u003cp\u003eINLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference.\u003c\/p\u003e\u003cp\u003e\u003ci\u003eBayesian Regression Modeling with INLA \u003c\/i\u003ecovers a wide range of modern regression models and focuses on the INLA technique for building Bayesian models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to demonstrate the interplay of theory and practice with reproducible studies. Complete R commands are provided for each example, and a supporting website holds all of the data described in the book. An R package including the data and additional functions in the book is available to download. The book is aimed at readers who have a basic knowledge of statistical theory and Bayesian methodology. It gets readers up to date on the latest in Bayesian inference using INLA and prepares them for sophisticated, real-world work.\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":54232697700696,"sku":"9780367572266","price":64.99,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0278\/1295\/4195\/files\/9780367572266.jpg?v=1780988451","url":"https:\/\/agendabookshop.com\/products\/bayesian-regression-modeling-with-inla-1","provider":"Agenda Bookshop","version":"1.0","type":"link"}