Bayes Inference R

Simulation and Inference for Stochastic Processes with YUIMA  eBooks & eLearning

Posted by AvaxGenius at June 4, 2018
Simulation and Inference for Stochastic Processes with YUIMA

Simulation and Inference for Stochastic Processes with YUIMA: A Comprehensive R Framework for SDEs and Other Stochastic Processes By Stefano M. Iacus
English | PDF,EPUB | 2018 | 277 Pages | ISBN : 3319555677 | 12.31 MB

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on.
"Probabilistic Models of the Brain: Perception and Neural Function" ed. by R.P.N. Rao, B.A. Olshausen, M.S. Lewicki

"Probabilistic Models of the Brain: Perception and Neural Function" ed. by Rajesh P.N. Rao, Bruno A. Olshausen, Michael S. Lewicki
Neural Information Processing Series
BB / MIT Press | 2002 | ISBN: 0585437122 9780585437125 | 335 pages | PDF | 3 MB

The book presents top-down computational models as well as bottom-up neurally motivated models of brain function. The topics covered include Bayesian and information-theoretic models of perception, probabilistic theories of neural coding and spike timing, computational models of lateral and cortico-cortical feedback connections, and the development of receptive field properties from natural signals.

Learning Bayesian Models with R (Repost)  eBooks & eLearning

Posted by insetes at Oct. 13, 2017
Learning Bayesian Models with R (Repost)

Learning Bayesian Models with R By Dr. Hari M. Koduvely
2015 | 168 Pages | ISBN: 178398760X | EPUB | 3 MB

Learning Bayesian Models with R  eBooks & eLearning

Posted by readerXXI at Oct. 6, 2017
Learning Bayesian Models with R

Learning Bayesian Models with R
by Dr. Hari M. Koduvely
English | 2015 | ISBN: 178398760X | 168 Pages | Mobi+Code Files | 6.5 MB

Learning Bayesian Models with R  eBooks & eLearning

Posted by readerXXI at April 10, 2017
Learning Bayesian Models with R

Learning Bayesian Models with R
by Dr. Hari M. Koduvely
English | 2015 | ISBN: 178398760X | 165 Pages | True PDF | 1.48 MB

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems.

Introductory Statistical Inference (Repost)  eBooks & eLearning

Posted by nebulae at Dec. 14, 2016
Introductory Statistical Inference (Repost)

Nitis Mukhopadhyay, "Introductory Statistical Inference"
English | ISBN: 1574446134 | 2006 | 304 pages | PDF | 4 MB

Learning Bayesian Models with R (Repost)  eBooks & eLearning

Posted by enmoys at May 26, 2016
Learning Bayesian Models with R (Repost)

Learning Bayesian Models with R By Dr. Hari M. Koduvely
2015 | 168 Pages | ISBN: 178398760X | EPUB | 3 MB

Examples in Parametric Inference with R  eBooks & eLearning

Posted by Underaglassmoon at May 24, 2016
Examples in Parametric Inference with R

Examples in Parametric Inference with R
Springer | Statistical Theory and Methods | June 21, 2016 | ISBN-10: 9811008884 | 529 pages | pdf | 3.97 mb

Authors: Dixit, Ulhas Jayram
Exclusively focuses on statistical inference
Presents sophisticated mathematical proofs in a simple and easy-to-follow language
Discusses fundamental topics common to many fields of statistical inference, and which offer a point of departure for in-depth study

Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory  eBooks & eLearning

Posted by DZ123 at Nov. 2, 2015
Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory

John Earman, "Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory"
English | 1992 | ISBN: 0262050463 | DJVU | pages: 287 | 1,9 mb

Learning Bayesian Models with R  eBooks & eLearning

Posted by AlenMiler at Oct. 30, 2015
Learning Bayesian Models with R

Learning Bayesian Models with R by Dr. Hari M. Koduvely
English | 28 Oct. 2015 | ISBN: 178398760X | 168 Pages | AZW3 (Kindle)/HTML/EPUB/PDF (conv) | 19 MB

This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications.