Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Wiley | Mechanical Engineering | December 12 2016 | ISBN-10: 1119153034 | 248 pages | pdf | 6.23 mb
by Tshilidzi Marwala (Author), Ilyes Boulkaibet (Author), Sondipon Adhikari (Author)
Dana Kelly, Curtis Smith, "Bayesian Inference for Probabilistic Risk Assessment: A Practitioner's Guidebook" Publisher: S.r.n.e. | ISBN: 1849961867 | October 28, 2011 | PDF | 240 pages | 4 MB
Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described.
Bayesian Data Analysis for Animal Scientists: The Basics By Prof. Dr. Agustín Blasco English | PDF | 2017 | 287 Pages | ISBN : 3319542737 | 6.58 MB
In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biologist or the agricultural researcher does not normally have a background in Bayesian statistics, having difficulties in following the technical books introducing Bayesian techniques.
Data Analysis: A Bayesian Tutorial by Devinderjit Sivia, John Skilling Language: English | 2006 | ISBN: 0198568320 | 264 pages | PDF | 5,85 MB
Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.