Probability and statistics

Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct.

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics.

In a world where artificial intelligence is reshaping industries, how can we ensure that AI enhances human skills rather than replacing them?

Fierce global competition in manufacturing has made proficient facilities planning a mandatory issue in industrial engineering and technology.

Analyze Repeated Measures Studies Using Bayesian TechniquesGoing beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint.

Praise for the first edition:"e;[This book] succeeds singularly at providing a structured introduction to this active field of research.

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software.

This book presents recent advances in branching Brownian motion from the perspective of extreme value theory and statistical physics, for graduates.

Recognized as a "e;Recommended"e; title by Choice for their October 2020 issue.

When Prof.

This book provides an overview of several components of mesoscale modeling: boundary conditions, subgrid-scale parameterization, moisture processes, and radiation.

Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course.

Quantitative thinking is our inclination to view natural and everyday phenomena through a lens of measurable events, with forecasts, odds, predictions, and likelihood playing a dominant part.

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This book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society’s international conference on “Statistics for Innovation”, SIS 2025, held in Genoa, Italy, June 16-18, 2025.

This book presents some post-estimation and predictions strategies for the host of useful statistical models with applications in data science.

This textbook shows how to bring theoretical concepts from finance and econometrics to the data.

An accessible introduction to coalgebra, with clear mathematical explanations and numerous examples and exercises.

This book presents the refereed proceedings of the 15th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held in Linz, Austria, and organized by the Johannes Kepler University Linz and the Austrian Academy of Sciences, in July 2022.

Quantum mechanics is arguably one of the most successful scientific theories ever and its applications to chemistry, optics, and information theory are innumerable.

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations.

Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional.

From the reviews to the first edition:Most of the literature about stochastic differentialequations seems to place so much emphasis on rigor andcompleteness that it scares the nonexperts away.

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities.

The general topic of this book is the ergodic behavior of Markov processes.

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist.

Stochastic geometry, based on current developments in geometry, probability and measure theory, makes possible modeling of two- and three-dimensional random objects with interactions as they appear in the microstructure of materials, biological tissues, macroscopically in soil, geological sediments etc.

This book deals with a number of mathematical topics that are of great importance in the study of classical econometrics.

This volume constitutes the refereed proceedings of theSecond International Workshop on Advanced Methodologies for Bayesian Networks,AMBN 2015, held in Yokohama, Japan, in November 2015.

Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas.

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity.

In this book, prominent social scientists describe quantitative models in economics, history, sociology, political science, and psychology.

Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary.

This book provides an overview of Data Monitoring Committees(DMC) - what was done in the past, what is currently being done, and thoughts on improvements for the future.

The standard approach of most introductory books for practical statistics is that readers first learn the minimum mathematical basics of statistics and rudimentary concepts of statistical methodology.

An updated edition of the invaluable textbook on the concepts and practical application of nonlife actuarial models.

MATRIX is Australia's international and residential mathematical research institute.

Through simple, practical approaches, Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and Methods helps Six Sigma black belts and engineers successfully interpret warranty data to make accurate predictions.

Praise for Linear Models with R:This book is a must-have tool for anyone interested in understanding and applying linear models.

This book covers applications of machine learning in artificial intelligence.

This revised edition offers an approach to information theory that is more general than the classical approach of Shannon.

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

Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas.

N-of-1 trials, a type of individualized randomized controlled trial, are relevant to almost every discipline in medicine and psychology.

Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers.

Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability.

This book addresses the underlying foundational elements, both theoretical and methodological, of sponsored search.

Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear LtandLo.

This book explores multivariate statistics from both traditional and modern perspectives.