Bayesian Methods for Statistical Analysis (Borek Puza)

0.0 (0)
Bayesian Methods for Statistical Analysis (Borek Puza)

A book on statistical techniques for analyzing a wide range of data is called Bayesian approaches for statistical analysis.

The book is divided into 12 chapters that cover a wide range of topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling, and nonignorable nonresponse. The book begins with fundamental concepts and moves on to more advanced ideas.

Numerous tasks are included in the book, all of which have working solutions that include the entire computer code. With three hours of lectures and one tutorial each week for 13 weeks, it is appropriate for independent study or a semester-long course.

Ebook Details

About the Authors
In the Research School of Finance, Actuarial Studies, and Statistics, Dr. Borek Puza teaches statistics. He holds a BSc in Mathematics and a Ph.D., Master's, and Graduate Diploma in Statistics.
Published Date / Year
(September 15, 2017)
Creative Commons
698 pages
eBook Format
PDF (697 pages, 6.4 MB)

Similar Programming & Computer Books

Strategic Foundations of General Equilibrium: Dynamic Matching and Bargaining Games (Douglas Gale)
Since Adam Smith's day, the theory of competition has played a significant role in economic study. This book, published by one of the most eminent modern economic theorists, details...
The Pure Logic Of Choice (Richard D. Fuerle)
A broad theory of economics based on free will is presented in this free programming book. The assumption that humans have free will and the ability to alter physical...
Portfolio Theory and Financial Analyses (Robert Alan Hill)
Whether they involve calculating the return on a portfolio, analyzing portfolio risk, or assessing the effectiveness of the portfolio management process, this free programming book links each of the...
Price Theory: An Intermediate Text (David D. Friedman)
In order to help the reader grasp the economic way of thinking, the author first gives verbal, intuitive explanations of the topics before using graphs and/or calculus to illustrate...
Mathematical Models in Portfolio Analysis (Farida Kachapova)
This free programming book presents the mathematical theory of portfolio modeling in financial mathematics as a coherent whole, with justifications for each step. ...
Stochastic Calculus and Finance (Steven E. Shreve)
The first 10 years of the Carnegie Mellon Professional Master program in Computational Finance led to the development of stochastic calculus for finance. Students with calculus and probability based...
Math for Trades: Volume 1 (Chad Flinn, et al.)
The foundational elements for learning math are presented in this volume. Whole numbers, fractions, decimals, and percents are all included in the book. ...
Multimedia Fingerprinting Forensics for Traitor Tracing (K. J. Ray Liu, et al)
The widespread dissemination and consumption of digital multimedia data is a result of the appeal of multimedia content.
Bayes Factors for Forensic Decision Analyses with R (Silvia Bozza, et al)
With the help of the R programming language, this book offers a self-contained introduction to computational Bayesian statistics. This free programming book, which primarily focuses on Bayes factors supported...
Computational and Numerical Simulations (Jan Awrejcewicz)
The edited book Computational and Numerical Simulations has 20 chapters. The book discusses contemporary work on numerical simulations of engineering and physical systems. ...

User reviews

There are no user reviews for this listing.
Rate this Book