عنوان
پدید آورنده
موضوع
رده
QA278.2 .W36 2018eb
QA278
.
2
.
W36
2018eb
کتابخانه
محل استقرار
1351165747
1351165763
1498727263
9781351165747
9781351165761
9781498727266
1498727255
9781498727259
Bayesian regression modeling with INLA /
[Book]
Xiaofeng Wang, Cleveland Clinic, Cleveland, Ohio ; Yu Yue, Baruch College, the City University of New York ; Julian J. Faraway, University of Bath, UK.
Boca Raton :
CRC Press,
[2018]
©2018
1 online resource (xii, 312 pages)
Chapman & Hall/CRC Computer Science & Data Analysis
Includes bibliographical references and index.
Introduction -- Theory of INLA -- Bayesian linear regression -- Generalized linear models -- Linear mixed and generalized linear mixed models -- Survival analysis -- Random walk models for smoothing methods -- Gaussian process regression -- Additive and generalized additive models -- Errors-in-variables regression -- Miscellaneous topics in INLA.
0
"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."--Provided by publisher.
Ingram Content Group
9781351165747
Bayesian regression modeling with INLA.
9781498727259
Bayesian regression modeling with integrated Laplace approximation
Bayesian statistical decision theory.
Gaussian processes.
Laplace transformation.
Regression analysis.
Bayesian statistical decision theory.
Gaussian processes.
Laplace transformation.
MATHEMATICS-- Applied.
MATHEMATICS-- Probability & Statistics-- General.
Regression analysis.
MAT-- 003000
MAT-- 029000
519
.
5/42
23
QA278
.
2
.
W36
2018eb
Wang, Xiaofeng, (Professor of medicine)
Faraway, Julian James
Yue, Yu,1981-
20200822175235.0
pn
مطالعه متن کتاب [Book]
Y
