Bayesian Inference

An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling br...

The implementation problem lies at the heart of a theory of institutions. Simply stated, the aim of implementation theory is to investigate in a ri...

The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of ...

A thorough grounding in Markov chains and martingales is essential in dealing with many problems in applied probability, and is a gateway to the mo...

Reliability and maintenance modeling with optimization is the most fundamental and interdisciplinary research area that can be applied to every tec...

Based on the authors lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical infer...

This book is about the interplay between chance and order, but limited to mostly binary events, such as success/failure as they occur in a diversit...

This textbook will continue to be the best suitable textbook written specifically for a first course on probability theory and designed for industr...

This book explains the importance of using the probability that the hypothesis is correct (PHC), an intuitive measure that anyone can understand, a...

This book introduces the concept of bespoke learning, a new mechanistic approach that makes it possible to generate values of an output variable at...

There has been a tremendous increase in the breadth of application of Bayesian methods to problems in industry in the last twenty or so years. Howe...

This book examines statistical models for frequency data.  The primary focus is on log-linear models for contingency tables but also includes exten...

This graduate textbook on the statistical approach to data science describes the basic ideas, scientific principles and common techniques for the e...

This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applicat...

The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in...

We live in the era of big data. However, small data sets are still common for ethical, financial, or practical reasons. Small sample sizes can caus...

We live in the era of big data. However, small data sets are still common for ethical, financial, or practical reasons. Small sample sizes can caus...

Uncertainty quantification is an important step in establishing the predictive accuracy of simulation models employed in a broad range of disciplin...

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing...

A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering...

This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-M...

Fine-tune your marketing research with this cutting-edge statistical toolkit Bayesian Statistics and Marketing illustrates the potential for apply...

Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teachin...

Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teachin...

Bayesian analysis is today understood to be an extremely powerful method of statistical analysis, as well an approach to statistics that is particu...

The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues ...

This book walks you through learning probability and statistics from a Bayesian point of view.  From an introduction to probability theory throu...

This book walks you through learning probability and statistics from a Bayesian point of view.  From an introduction to probability theory throu...

Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated the...

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book...

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book...

Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting. The framew...

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use direct...