Freely available in its PDF form from the author's website: faculty.marshall.usc.edu/gareth-james/ISL/
Contributors: Franzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, Pius Korner-Nievergelt Bayesian Data Analysis in Ecology Using …
The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important …
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that …
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that …
Researchers in many branches of science are increasingly coming into contact with Bayesian statistics or Bayesian probability theory. This book …
The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data …
This is the first text to examine the use of statistical methods in forensic science and bayesian statistics in combination. …
This book is not really a tutorial for beginners as it goes directly into the subject. It is well written, …
This book provides a multi-level introduction to Bayesian reasoning (as opposed to ''conventional statistics'') and its applications to data analysis. …
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis …
Drawing from the authors’ own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: …
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice …
Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists …
For his excellent monograph, David Ardia won the Chorafas prize 2008 at the University of Fribourg Switzerland.This book presents methodologies …
A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look …
This second, much enlarged edition by Lehmann and Casella of Lehmann's classic text on point estimation maintains the outlook and …
Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python About This BookGain in-depth knowledge …
"Introduction to Applied Bayesian Statistics and Estimation for Social Scientists' covers the complete process of Bayesian statistical analysis in great …
Dr. Scott Lynch has made a great job for those (like me) who want a clear introduction to the methods …
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity …
This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been …
This volume has its origin in the third ·Workshop on Maximum-Entropy and Bayesian Methods in Applied Statistics,· held at the …
Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated …
Probability as an Alternative to Boolean Logic While logic is the mathematical foundation of rational reasoning and the fundamental principle …
I bought this book a while ago for self-study (before the reviews saying "not good for self-study") but my attempt …
This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the …
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