Author: Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 302
Book Description
The fortran programming of classical and Bayesian transition probability estimators
Author: Contributions to Economic Analysis
Author: T.C. LeePublisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 264
Book Description
Scientific and Technical Aerospace Reports
Author: Publications of Staff Members
Author: Michigan State UniversityPublisher:
ISBN:
Category :
Languages : en
Pages : 58
Book Description
Statistics and Econometrics
Author: Joseph ZarembaPublisher: Gale Cengage
ISBN:
Category : Business & Economics
Languages : en
Pages : 728
Book Description
Mathematical Reviews
Author: Computational Bayesian Statistics
Author: M. Antónia Amaral TurkmanPublisher: Cambridge University Press
ISBN: 1108481035
Category : Business & Economics
Languages : en
Pages : 256
Book Description
This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.
Introducing Monte Carlo Methods with R
Author: Christian RobertPublisher: Springer Science & Business Media
ISBN: 1441915753
Category : Computers
Languages : en
Pages : 297
Book Description
This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Bayesian Essentials with R
Author: Jean-Michel MarinPublisher: Springer Science & Business Media
ISBN: 1461486874
Category : Computers
Languages : en
Pages : 305
Book Description
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable. Bayesian Essentials with R can be used as a textbook at both undergraduate and graduate levels. It is particularly useful with students in professional degree programs and scientists to analyze data the Bayesian way. The text will also enhance introductory courses on Bayesian statistics. Prerequisites for the book are an undergraduate background in probability and statistics, if not in Bayesian statistics.
The Software Catalog
Author: MENU StaffPublisher: Elsevier Science & Technology
ISBN:
Category : Science
Languages : en
Pages : 726
Book Description