Probability and statistics

Ageing and dependence are two important characteristics in reliability and survival analysis, and they affect significantly the decision people make with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas.

Introduction to Computational Engineering with MATLAB(R) aims to teach readers how to use MATLAB programming to solve numerical engineering problems.

A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.

This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments.

Helps Students Understand Mathematical Programming Principles and Solve Real-World ApplicationsSupplies enough mathematical rigor yet accessible enough for undergraduatesIntegrating a hands-on learning approach, a strong linear algebra focus, Maple software, and real-world applications, Linear and Nonlinear Programming with Maple : An Interactive,

This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty.

Future predictions are always a topic of interest.

This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management.

Scan statistics, one of the most active research areas in applied probability and statistics, has seen a tremendous growth during the last 25 years.

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.

This text is an introduction to the modern theory and applications of probability and stochastics.

This book, dedicated to Winfried Stute on the occasion of his 70th birthday, presents a unique collection of contributions by leading experts in statistics, stochastic processes, mathematical finance and insurance.

This book deals with extreme value theory for univariate and multivariate time series models characterized by power-law tails.

This book covers the following subjects: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.

The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word.

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment's efficacy.

Originally published in 1981.

How do you learn about what's going on in the world?

This book presents the state of the art in extreme value theory, with a collection of articles related to a seminal paper on the bivariate extreme value distribution written by Professor Masaaki Sibuya in 1960, demonstrating various developments of the original idea over the last half-century.

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation.

R is rapidly becoming the standard software for statistical analyses, graphical presentation of data, and programming in the natural, physical, social, and engineering sciences.

Comprehensive, yet concise, this textbook is the go-to guide to learn why probability is so important and its applications.

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.

This book examines several epistemological regimes in studies of numerical data over the last four centuries.

This contributed volume explores the emerging intersection between big data analytics and genomics.

This book discusses mixture and hidden Markov models for modeling behavioral data.

This book is a state of the art treatise on what has been done so far on measuring sustainability for decision making.

Computational intelligence consists of those techniques that imitate the human brain and nature to adopt the decision-making approach.

In the years since the publication of the best-selling first edition, the incorporation of ideas and theories from the rapidly growing field of financial economics has precipitated considerable development of thinking in the actuarial profession.

This is the first technical book that considers tests as public tools and examines how to engineer and process test data, extract the structure within the data to be visualized, and thereby make test results useful for students, teachers, and the society.

Motivated by the many and long-standing contributions of H.

Risk or uncertainty assessments are used as aids to decision making in nearly every aspect of business, education, and government.

Newly revised to specifically address Microsoft Excel 2019, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems.

Praise for the First Edition "e;This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic.

This book constitutes the refereed proceedings of the 16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2019, held in Milan, Italy, in September 2019.

This book constitutes the thoroughly refereed proceedings of the 26th International Conference on Computer Networks, CN 2019, held in Gliwice, Poland, in June 2019.

The book, belonging to the series "e;Studies in Theoretical and Applied Statistics- Selected Papers from the Statistical Societies"e;, presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "e;Advances in Latent Variables.

Calculus for Business and Economics: An Example-Based Introduction is designed for first-year university students specializing in business and economics.

Fixed point theory in probabilistic metric spaces can be considered as a part of Probabilistic Analysis, which is a very dynamic area of mathematical research.

Refection Positivity is a central theme at the crossroads of Lie group representations, euclidean and abstract harmonic analysis, constructive quantum field theory, and stochastic processes.

Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience.

The most comprehensive and applied discussion of stated choice experiment constructions available The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making.

Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies.

Despite research interest in functional data analysis in the last three decades, few books are available on the subject.

White noise analysis is an advanced stochastic calculus that has developed extensively since three decades ago.