Probability and statistics

This book presents modern methods and real-world applications of compositional data analysis.

Inventory management is concerned with matching supply with demand and a central problem in Operations Management.

The purpose of this monograph is to provide a theory of Markov processes that are invariant under the actions of Lie groups, focusing on ways to represent such processes in the spirit of the classical Levy-Khinchin representation.

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Research data management is becoming more complicated.

Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis.

The urgent need to describe and to solve certain problems connected to extreme phenomena in various areas of applications has been of decisive influence on the vital development of extreme value theory.

In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics.

The aim of the Workshop was to bring together scientists involved in approaching topical problems in mathematical physics by probabilistic methods.

This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

This book is a comprehensive guide to methodologies for analyzing reliability and optimizing maintenance in complex systems, spanning from initial design to operational stages.

Peter P.

Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines.

A classical queueing model consists of three parts - arrival process, service process, and queue discipline.

This book compiles and presents new developments in statistical causal inference.

This collection of articles is dedicated to Frank Spitzer on the occasion of his 65th birthday.

This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R.

This study analyses the newly available statistical evidence on income distribution in the former Soviet Union both by social group and by republic, and considers the significance of inequalities as a factor contributing to the demise of the Communist regime.

A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis.

The use of probabilistic methods in the biological sciences has been so well established by now that mathematical biology is regarded by many as a distinct dis- cipline with its own repertoire of techniques.

Paradoxes are poems of science and philosophy that collectively allow us to address broad multidisciplinary issues within a microcosm.

Foundational questions in logic, mathematics, computer science and physics are constant sources of epistemological debate in contemporary philosophy.

Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes.

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle.

This second edition focuses on the application of statistical methods in the field of hydrology and hydroclimatology.

This volume features original contributions and invited review articles on mathematical statistics, statistical simulation and experimental design.

Stochastic processes occur everywhere in the sciences, economics and engineering, and they need to be understood by (applied) mathematicians, engineers and scientists alike.

Despite the fact that, for most of us, time is a central focus of our lives, the examination of what we do with our time and why has received limited attention as a method for understanding human behavior in the social sciences.

The book presents a collection of peer-reviewed short papers selected from those presented at the International Conference Mathematical and Statistical Methods for Actuarial Sciences and Finance - MAF2024.

Stochastic Integrals discusses one area of diffusion processes: the differential and integral calculus based upon the Brownian motion.

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research.

This is the very first comprehensive monograph in a burgeoning, new research area - the theory of cooperative game with incomplete information with emphasis on the solution concept of Bayesian incentive compatible strong equilibrium that encompasses the concept of the Bayesian incentive compatible core.

This book developed from a course given by the author to undergraduate and postgraduate students.

All the Essentials to Start Using Adaptive Designs in No TimeCompared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time.

This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.

This book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs.

This book provides a comprehensive guide to econometric modeling, combining theory with practical implementation using Python.

Astrostatistical Challenges for the New Astronomy presents a collection of monographs authored by several of the disciplines leading astrostatisticians, i.

This research monograph summarizes a line of research that maps certain classical problems of discrete mathematics and operations research - such as the Hamiltonian Cycle and the Travelling Salesman Problems - into convex domains where continuum analysis can be carried out.

The Handbook of Health Services Research is a reference for all aspects of the field of health services and outcomes research.

This text on logistic regression methods contains the following eight chapters: 1 Introduction to Logistic Regression 2 Important Special Cases of the Logistic Model 3 Computing the Odds Ratio in Logistic Regression 4 Maximum Likelihood Techniques: An Overview 5 Statistical Inferences Using Maximum Likelihood Techniques 6 Modeling Strategy Guidelines 7 Modeling Strategy for Assessing Interaction and Confounding 8 Analysis of Matched Data Using Logistic Regression Each chapter contains a presentation of its topic in "e;lecture-book"e; format together with objectives, an outline, key formulae, practice exercises, and a test.

This book aims not only to introduce fundamental biostatistics topics but to explain them through R-project (R-studio).