Probability and statistics

A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach.

Presents a new approach to causal inference and explanation, addressing both the timing and complexity of relationships.

This handbook presents the basic aspects of actuarial loss reserving.

This book provides a very elementary introduction to K-theory for C*-algebras, and is ideal for beginning graduate students.

This book provides clinical medicine readers with a detailed explanation of statistical concepts using non-technical terms.

This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.

Limit theorems for random sequences may conventionally be divided into two large parts, one of them dealing with convergence of distributions (weak limit theorems) and the other, with almost sure convergence, that is to say, with asymptotic prop- erties of almost all sample paths of the sequences involved (strong limit theorems).

Data visualization is the art and science of making information visible.

Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or absolutely regular.

Commissioned by the Statistical Society of Canada (SSC), Statistics in Action: A Canadian Outlook helps both general readers and users of statistics better appreciate the scope and importance of statistics.

In the decade since its publication, the first edition of Statistics for Archaeologists has become a staple in the classroom.

Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining.

The final volume of this series presents a synopsis of the curriculum that a typical Six Sigma program should follow.

A How-To Guide for Conducting Common Fisheries-Related Analyses in RIntroductory Fisheries Analyses with R provides detailed instructions on performing basic fisheries stock assessment analyses in the R environment.

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions.

This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment.

From foundations to state-of-the-art; the tools and philosophy you need to build network models.

This highly motivating introduction to statistical learning machines explains underlying principles in nontechnical language, using many examples and figures.

This book is especially relevant to undergraduates, postgraduates and researchers studying quantitative techniques as part of business, management and finance.

This book constitutes the proceedings of the 13th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2022, held in conjunction with the 25th MICCAI conference.

This volume contains detailed, worked-out notes of six main courses given at the Saint-Flour Summer Schools from 1985 to 1987.

Objecti'ves.

Teaches students how to use Stata to conduct the statistical analyses most commonly used in political science.

This book investigates the mathematical analysis of biological invasions.

This concise and up-to-date textbook provides an accessible introduction to the core concepts of nonlinear dynamics as well as its existing and potential applications.

This book develops the theory of statistical inference in statistical models with an infinite-dimensional parameter space, including mathematical foundations and key decision-theoretic principles.

Achieve faster, more efficient heterogeneous network design and optimization with this comprehensive guide.

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

This book collects important advances in methodology and data analysis for directional statistics.

The problem of selection of alternatives or the problem of decision making in the modern world has become the most important class of problems constantly faced by business people, researchers, doctors and engineers.

Currently, the techniques of operation research are widely used in every aspect of day-to-day life.

This book presents a detailed description of the development of statistical theory.

Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference.

Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint.

Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks.

Photogrammetry is a science based technology with more than a century of history and development.

This Third Edition updates the "e;Solutions Manual for Econometrics"e; to match the Fifth Edition of the Econometrics textbook.

A Novel Method to Analyze Problems and Encourage Systemic ThinkingReal-Life Case Studies Illustrate the Application of the Systemic Yoyo Model in Diverse AreasWritten by the co-creator of the systemic yoyo model, Systemic Yoyos: Some Impacts of the Second Dimension shows how the yoyo model and its methodology can be employed to study many unsettled

This straightforward primer in basic statistics and epidemiology emphasises their practical use in healthcare and public health, providing understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research.

The purpose of this book is to thoroughly prepare diverse areas of researchers in quantification theory.

Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets.

In this monograph the narrow topology on random probability measures on Polish spaces is investigated in a thorough and comprehensive way.

The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solveproblems in quantitative Genetic Epidemiology Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems.

At the end of 1960s and the beginning of 1970s, when the Russian version of this book was written, the 'general theory of random processes' did not operate widely with such notions as semimartingale, stochastic integral with respect to semimartingale, the Ito formula for semimartingales, etc.

1.

Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states.