Quantum mechanics is arguably one of the most successful scientific theories ever and its applications to chemistry, opt......more

This book is a useful overview of results in multivariate probability distributions and multivariate analysis as well as......more

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and fro......more

Revised edition of: Statistical methods / Rudolf J. Freund, William J. Wilson, Donna L. Mohr. 3rd ed. c2010....more

A First Step toward a Unified Theory of Richly Parameterized Linear Models Using mixed linear models to analyze data oft......more

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfie......more

How can major corporations and governments more quickly and accurately detect and address cyberattacks on their networks......more

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually refe......more

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible......more

This is a book about statistical distributions, their properties, and their application to modelling the dependence of t......more

This textbook considers statistical learning applications when interest centers on the conditional distribution of a res......more

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to a......more

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out ......more

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological......more

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The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emp......more

The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts f......more

Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-b......more

If you are a manager who receives the results of any data analyst’s work to help with your decision-making, this book is......more

Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions o......more

Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations a......more

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Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently th......more

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models......more

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The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to con......more

The study of animal movement has always been a key element in ecological science, because it is inherently linked to cri......more

If you know a little bit about financial mathematics but don’t yet know a lot about programming, then C++ for Financial ......more

The apparent contradiction between statistical significance and biological relevance has diminished the value of statist......more

Achieve Technological Advancements in Applied Science and Engineering Using Efficient Experiments That Consume the Least......more

Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the......more

Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas......more

Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA) A relatively new are......more

A Sound Basis for the Theory of Statistical Inference Measuring Statistical Evidence Using Relative Belief provides an o......more

This book addresses many of the gaps in how industry and academia are currently tackling problems associated with big da......more

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Chapter 1: Mechanics of Random Motion.- Chapter 2: Applications.- Chapter 3: Momentum, Kinetic Energy, Locality.- Chapte......more

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This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explor......more

This book brings together two major trends: data science and blockchains. It is one of the first books to systematically......more

Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods a......more

Many experiments have shown the human brain generally has very serious problems dealing with probability and chance. A g......more

Chapter 1. Machine Learning Based Ensemble Approach for Predicting the Mortality Risk of Covid-19 Patients: A Case Study......more

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) ......more

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) ......more

Are you buying a car or smartphone or dishwasher? We bet long-term, trouble-free operation (i.e., high reliability) is a......more

This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the......more

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The book outlines the processes of calculating and critically reviewing construction costs and times for clients and con......more

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Preface.- List of Contributors .- 1 An introduction to the (postponed) 5th edition of the International Workshop on Func......more

This textbook, now in its fourth edition, offers a rigorous and self-contained introduction to the theory of continuous-......more

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In this book, the optimal transportation problem (OT) is described as a variational problem for absolutely continuous st......more

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This text provides an introduction to the applications and implementations of partial differential equations. The conten......more

This book first presents an overview of the history of a national character survey by the Institute of Statistical Mathe......more

This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Determini......more

This book contains new aspects of model diagnostics in time series analysis, including variable selection problems and h......more

Chapter 1: Why Urban Analysis.- Chapter 2: The research process. Chapter 3: Secondary data.- Chapter 4: Conducting surve......more

This book presents the state of the art in extreme value theory, with a collection of articles related to a seminal pape......more

This authoritative state-of-the-art account of probability on networks for graduate students and researchers in mathemat......more

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This book covers methods of Mathematical Morphology to model and simulate random sets and functions (scalar and multivar......more

Preface.- J.J. Egozcue and W.L. Maldonado: An interpretable orthogonal decomposition of positive square matrices.- Part ......more

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