Probability and statistics Books

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 text or as a source of reference. It is widely used for teaching statistics in schools.

This book provides one of the first unified accounts of the dynamic aspects involved in the strategic behavior in queues. The author presents the material in an easy style with mostly non-technical language, emphasizing models and qualitative insights...

Using a wide range of OR optimization examples, this book demonstrates how the OR procedures in SAS work. The text is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project...

This book considers the problem of estimating the percent of nonconforming items in a process from the ground up. It examines methods based on both attribute data and variable data. For variable data, it looks at the basic techniques that were initially...

The aim of Understanding Analytic Hierarchy Process book is to provide the reader with a critical guide to AHP. In this book, the AHP method is considered primarily as a mathematical technique supporting the decision-making process. 

In the view of many probabilists, author Anatolii Puhalskii's research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the...

Maschinelles Lernen prägt zunehmend unseren Alltag, doch fehlt bislang eine Fachdidaktik, die das Thema als Lerngegenstand für Schulen und Hochschulen systematisch untersucht. In der vorliegenden Arbeit werden Methoden der fachdidaktische...

This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The...

This book examines under what circumstances, and with which techniques, one can reasonably infer cause and effect in a business setting, and use the insight to drive business decisions. It is written at a level accessible to anyone with a master's degree...

Copula additive distributional regression enables the joint modeling of multiple outcomes, an essential aspect of many real-world research problems. This book provides an accessible overview of this modeling approach, with a particular focus on its...

Intended to provide a nearly comprehensive account of methods, theory, applications, as well as open problems related to robust SAE, that the monograph will help persuade practitioners, such as those in government agencies, to more readily adopt robust...

Data Analysis from Scratch.2 Books in 1Book 1: Basic Python in FinanceBook 2: Time Series in Python.....................

Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents...

Written by pioneers in an exciting new field, this book introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Grobner bases and a thorough description of their...

Incorporating a collection of recent results, Pólya Urn Models deals with discrete probability through the modern and evolving urn theory and its numerous applications. It looks at how some classical problems of discrete probability have roots in urn...

This book should serve as an invaluable and fascinating resource for university, college, and high school students who wish to extend their reading, as well as for teachers and lecturers who want to liven up their courses while retaining academic rigour.

Financial Modelling in Commodity Markets provides a basic and self-contained introduction to the ideas underpinning financial modelling of products in commodity markets.  

Bayesian methods in reliability cannot be fully utilized without understanding the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some...

This self-contained book offers an extensive state-of-the-art exposition of rotational integral geometry, a field that has reached significant maturity over the past four decades. Through a unified description of key results previously scattered across...

This book offers an extensive exploration of foundation models, guiding readers through the essential concepts and advanced topics that define this rapidly evolving research area. Designed for those seeking to deepen their understanding and contribute to...

Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this...

With many examples throughout and clear explanations of key concepts, this book focuses on the genetic interaction networks as a paradigm for interpreting the complexity of molecular biology at a genomic scale. The authors describe the experimental...

A bestseller for nearly 25 years, this book helps applied statisticians and researchers effectively analyze the kinds of nonstandard data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has...

Random sets as models for set-valued observations, are a new type of data proving useful in areas such as survey sampling, biostatistics, and intelligent systems. This is the first text to explore the topic in depth, using extended probability theory to...

From the reviews:"The first volume is devoted to ergodic theory and dynamical systems. It contains 19 papers divided into four groups ... . The reader will find a wealth of information and ideas that can still ignite inspiration and motivate students as...

An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and...

Risk theory, which deals with stochastic models of an insurance business, is a classical application of probability theory. The fundamental problem in risk theory is to investigate the ruin possibility of the risk business...

This IMA Volume in ~athematics and its Applications PERCOLATION THEORY AND ERGODIC THEORY OF INFINITE PARTICLE SYSTEMS represents the proceedings of a workshop which was an integral part of the 19R4-85 IMA program on STOCHASTIC...

This IMA Volume in Mathematics and its Applications RANDOM MEDIA represents the proceedings of a workshop which was an integral part of the 1984-85 IMA program on STOCHASTIC DIFFERENTIAL EQUATIONS AND THEIR APPLICATIONS We are...

Resampling methods-techniques for repeatedly resampling data to obtain results-are being used in virtually every research area. This practical guide discusses the applications of these methods in a wide variety of subject areas. Each chapter contains a...

This handbook presents many methodological advances and the latest applications of missing data methods in empirical research. It outlines a general taxonomy of missing data mechanisms and their implications for analysis and describes alternatives for...

Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference...

Adaptive clinical trial designs, unlike traditional fixed clinical trial designs, enable modification of studies in response to the data generated in the course of the trial. This often results in studies that are substantially faster, more efficient,...

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design,...

This book presents innovative approaches in Receiver Operating Characteristic (ROC) analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics. The covered topics include...

Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis. The R Primer provides a collection of concise examples and...

Improving Your NCAA® Bracket with Statistics is both an easy-to-use tip sheet to improve your winning odds and an intellectual history of how statistical reasoning has been applied to the bracket pool using methods standard and innovative.

The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. This work demonstrates how practical problems in science, industry, and trade can be solved using this method. It presents various examples of its...

A step-by-step guide for anyone challenged by the many subtleties of sampling particulate materials. The only comprehensive document merging the famous works of P. Gy, I. Visman, and C.O. Ingamells into a single theory in a logical way - the most...

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack the statistical skills or resources that would allow them to explore their data to its full potential...

This book is intended for anyone who is considering a career in statistics or a related field, or those at any point in their career with sufficient work time remaining such that investing in additional learning could be beneficial. As such, the book...

Fourth edition has new chapters on Bayesian survival analysis and use of the R software. Chapters extensively revised, expanded to add new material on topics that include methods for assessing predictive ability of a model, joint models for longitudinal...

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United...

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United...

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United...