Probability & Statistics

In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilev...

This book provides a rigorous introduction to the theory, computation, and applications of variational inequalities (VIs), with a focus on applicat...

Using a new methodology for foresight studies, this book presents new findings and policy recommendations to improve living conditions and make pro...

This fully revised and updated second edition is an essential introduction to inferential statistics. It is the first introductory statistics text ...

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...

The unique compendium starts with a simplified version of the information theory which allows any beginner in math to embrace the mysterious concep...

Brownian motion is an important topic in various applied fields where the analysis of random events is necessary. Introducing Brownian motion from ...

This textbook presents measure theory in a concise yet clear manner, providing readers with a solid foundation in the mathematical axiomatic system...

Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from...

The main report of the UKAEA (United Kingdom Atomic Energy Authority) Working Group on the Risks to Society from Potential Major Accidents, with an...

Statisticians have met the need to test hundreds or thousands of genomics hypotheses simultaneously with novel empirical Bayes methods that combine...

Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular an...

Fixed Point Theory, Variational Analysis, and Optimization not only covers three vital branches of nonlinear analysisfixed point theory, variationa...

Process Capability Analysis: Estimating Quality presents a systematic exploration of process capability analysis and how it may be used to estimate...

Deep learning is an important element of artificial intelligence, especially in applications such as image classification in which various architec...

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack t...

Discrete phenomena are an important aspect of various complex systems, acting both as underlying driving mechanisms and as manifestations of divers...

Age-Period-Cohort analysis has a wide range of applications, from chronic disease incidence and mortality data in public health and epidemiology, t...

Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonpa...

Introduction to Probability with Texas Hold'em Examples illustrates both standard and advanced probability topics using the popular poker game of T...

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory and App...

A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of Statistical Algorithms: With Refe...

Learn how to read, understand, and write better SAS programs Understand the key differences between similar SAS syntax and programming approaches S...

Reliability is an essential concept in mathematics, computing, research, and all disciplines of engineering, and reliability as a characteristic is...

Utility-Based Learning from Data provides a pedagogical, self-contained discussion of probability estimation methods via a coherent approach from t...

Originally published in 1923 Chance and Error examines the vagaries of chance, and how this is the result of the interference of yes and no. The bo...

Statistical Methods: An Introduction to Basic Statistical Concepts and Analysis, Second Edition is a textbook designed for students with no prior t...

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of...

Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on pa...

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The boo...

Written by some major contributors to the development of this class of graphical models, Chain Event Graphs introduces a viable and straightforwar...

A textbook for a graduate course in the theory of distributions and related topics, for students of applied mathematics or theoretical physics. Int...

This volume serves as a comprehensive introduction to Time Series Analysis (TSA), used commonly in financial and engineering sciences, to demonstra...

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pa...

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

Subjective Well-Being and Social Media shows how, by exploiting the unprecedented amount of information provided by the social networking sites, it...

This book provides a guide to the elements of simulation in statistics, which will include developments and which may be used either as a teaching ...

Principles of Scientific Methods focuses on the fundamental principles behind scientific methods. The book refers to science in a broad sense, incl...