Probability and statistics

This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.

Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research.

This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome obstacles that could not be previously solved by methods such as regression and time series modelling in the areas of economics, meteorology, and transportation.

Les probabilités font partie de la vie du citoyen du XXI^e siècle, et ce, dans divers contextes et domaines – en santé pour la sélection d’un traitement, en gestion pour le choix d’un investissement, etc.

This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics, different financial problems, and other scenarios in which these recently developed statistical models have been applied in recent years.

Those who work in allied health professions and education aim to make people's lives better.

A complete and up-to-date discussion of optimal split plot and split block designs Variations on Split Plot and Split Block Experiment Designs provides a comprehensive treatment of the design and analysis of two types of trials that are extremely popular in practice and play an integral part in the screening of applied experimental designs--split plot and split block experiments.

This three-chapter volume concerns the distributions of certain functionals of Levy processes.

Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference.

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The book introduces basic risk concepts and then goes on to discuss risk management and analysis processes and steps.

This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs.

Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks.

This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations.

Statistics is a subject with a vast field of application, involving problems which vary widely in their character and complexity.

This book first presents an overview of the history of a national character survey by the Institute of Statistical Mathematics that has been conducted for more than 65 years.

This book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field.

This textbook discusses central statistical concepts and their use in business and economics.

Das Buch bietet eine Einführung in Wahrscheinlichkeitsmodelle und die Schätzung solcher Modelle auf der Grundlage von Beobachtungen.

Hardly a day goes by without news headlines concerning infectious disease threats.

Research in statistics education is an emerging field, with much of the work being published in diverse journals across many disciplines.

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms.

Reinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective.

Biosecurity: A Systems Perspective provides an overview of biosecurity as a system of related components, actors, and risks.

Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena.

This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level.

Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions.

The pioneering work of Gus Archie moved log interpretation into log analysis with the introduction of the equation that bears his name.

This book has two-fold aims.

As the development of medicines has become more globalized, the geographic variations in the efficacy and safety of pharmaceutical products need to be addressed.

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike.

Mathematical Techniques of Applied Probability, Volume 1: Discrete Time Models: Basic Theory provides information pertinent to the basic theory of discrete time models.

Fundamentals of Mathematical Statistics is meant for a standard one-semester advanced undergraduate or graduate-level course in Mathematical Statistics.

Development in Statistics, Volume 1 is a collection of papers that deals with theory and application of parameter estimation in stochastic differential systems, the comparative aspects of the study of ordinary time series, and real multivariate distributions.

This book summarizes the research of more than a decade.

This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment.

Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data.

The essential introduction to the theory and application of linear models now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts.

This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research.

This text presents modern developments in time series analysis and focuses on their application to economic problems.

This book was created with the goal of helping students transition from the theoretical and methodological concepts of statistical inference to their implementation on a computer.

A Course in Mathematical Statistics, Second Edition, contains enough material for a year-long course in probability and statistics for advanced undergraduate or first-year graduate students, or it can be used independently for a one-semester (or even one-quarter) course in probability alone.

This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models.

Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool.