Bayesian Analysis

Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition [Repost]

Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition by Osvaldo A. Martin
English | January 31, 2024 | ISBN: 1805127160 | True EPUB/PDF | 394 pages | 38.2/37.7 MB
Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition [Repost]

Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition by Osvaldo A. Martin
English | January 31, 2024 | ISBN: 1805127160 | True EPUB/PDF | 394 pages | 38.2/37.7 MB
Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition [Repost]

Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition by Osvaldo A. Martin
English | January 31, 2024 | ISBN: 1805127160 | True EPUB/PDF | 394 pages | 38.2/37.7 MB
Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition [Repost]

Bayesian Analysis with Python: A Practical Guide to Probabilistic Modeling, 3rd Edition by Osvaldo A. Martin
English | January 31, 2024 | ISBN: 1805127160 | True EPUB/PDF | 394 pages | 38.2/37.7 MB

Introduction to Bayesian Analysis Course with Python 2021  eBooks & eLearning

Posted by ELK1nG at July 16, 2021
Introduction to Bayesian Analysis Course with Python 2021

Introduction to Bayesian Analysis Course with Python 2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 88 lectures (12h 54m) | Size: 4.67 GB

Learn the concepts and practical side of using the Bayesian approach to estimate likely event outcomes.

The Oxford Handbook of Applied Bayesian Analysis  eBooks & eLearning

Posted by IrGens at Feb. 12, 2022
The Oxford Handbook of Applied Bayesian Analysis

The Oxford Handbook of Applied Bayesian Analysis (Oxford Handbooks) edited by Mike West, Anthony O' Hagan
English | May 13, 2010 | ISBN: 0199548900, 0198703171 | True EPUB/PDF | 896 pages | 47.7/13.4 MB

Bayesian Analysis for the Social Sciences  eBooks & eLearning

Posted by AvaxGenius at Oct. 17, 2022
Bayesian Analysis for the Social Sciences

Bayesian Analysis for the Social Sciences by Simon Jackman
English | PDF | 2009 | 596 Pages | ISBN : 0470011548 | 8.7 MB

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS – the most-widely used Bayesian analysis software in the world – and R – an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.

Bayesian Analysis for Population Ecology  eBooks & eLearning

Posted by arundhati at Nov. 24, 2020
Bayesian Analysis for Population Ecology

Ruth King, "Bayesian Analysis for Population Ecology "
English | ISBN: 1439811873 | 2009 | 456 pages | PDF | 3 MB

Bayesian Analysis with Python (3rd Edition)  eBooks & eLearning

Posted by hill0 at Feb. 2, 2024
Bayesian Analysis with Python (3rd Edition)

Bayesian Analysis with Python: A practical guide to probabilistic modeling
English | 2024 | ISBN: 1805127160 | 503 Pages | EPUB (True) | 44 MB

Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics  eBooks & eLearning

Posted by AvaxGenius at June 29, 2022
Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics

Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics by Nguyen Ngoc Thach
English | EPUB | 2022 | 865 Pages | ISBN : 3030986888 | 61.4 MB

This book overviews latest ideas and developments in financial econometrics, with an emphasis on how to best use prior knowledge (e.g., Bayesian way) and how to best use successful data processing techniques from other application areas (e.g., from quantum physics).