Bayesian Regression Modeling with INLA

von

Wang, XiaofengRyan Yue, YuFaraway, Julian J.

BuchGebunden

Verkaufsrang2681inMathematik

CHF117.50

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.

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Details

ISBN/GTIN978-1-4987-2725-9

ProduktartBuch

EinbandGebunden

Verlag

Taylor and Francis

Chapman and Hall/CRC

Erscheinungsdatum16.02.2018

Auflage1. A.

ReiheChapman & Hall/CRC Computer Science & Data Analysis

Seiten312 Seiten

SpracheEnglisch

MasseBreite 156 mm, Höhe 234 mm

Gewicht600 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.5929734

KatalogBuchzentrum

Datenquelle-Nr.24375038

KategorieNaturwissenschaften, Medizin, Informatik, Technik

SachgebietMathematik

Weitere Details

Reihe

Pattern Recognition Algorithms for Data Mining

Correspondence Analysis and Data Coding with Java and R

Design and Modeling for Computer Experiments

Semisupervised Learning for Computational Linguistics

Introduction to Data Technologies

Microarray Image Analysis

Bayesian Artificial Intelligence

Foundations of Statistical Algorithms

Visualization and Verbalization of Data

Music Data Analysis

Data Science Foundations

Exploratory Data Analysis with MATLAB

Microarray Image Analysis

Exploratory Multivariate Analysis by Example Using R

Chain Event Graphs