Probability and statistics

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming.

There are numerous advantages to using Bayesian methods in diagnostic medicine, which is why they are employed more and more today in clinical studies.

Images are all around us!

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup.

Mathematics is the basis of casino games, which are the bedrock of a $100 billion/year industry.

The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve.

Devoted to the growing impact of statistical methodology and statistical computing in industry the aim of this book is to link the three components: Statistics - industry - computers.

The authors of this Festschrift prepared these papers to honour and express their friendship to Klaus Ritter on the occasion of his sixtieth birthday.

The lectures that four authors present in this volume investigate core topics related to the accelerated expansion of the Universe.

This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world.

This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application.

This book is a collection of advanced research/survey papers by eminent research workers in the Recursion theory.

Drawing on the authors' substantial expertise in modeling longitudinal and clustered data, Quasi-Least Squares Regression provides a thorough treatment of quasi-least squares (QLS) regression-a computational approach for the estimation of correlation parameters within the framework of generalized estimating equations (GEEs).

This 5th edition of this popular graduate textbook presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory.

A fully revised and updated second edition of a popular undergraduate textbook on elementary probability theory.

This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics.

This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions-that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs.

Creating a rigorous mathematical theory of randomness is far from being complete, even in the classical case.

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Introducing a revolutionary new model for the statistical analysis of experimental data In this important book, internationally acclaimed statistician, Chihiro Hirotsu, goes beyond classical analysis of variance (ANOVA) model to offer a unified theory and advanced techniques for the statistical analysis of experimental data.

This book presents the statistical analysis of compositional data using the log-ratio approach.

Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions.

Sergio Albeverio gave important contributions to many fields ranging from Physics to Mathematics, while creating new research areas from their interplay.

Drawn from nearly four decades of Lawrence L.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world.

This volume teaches readers how to sort through the vast mountain of climate and environmental science data to extract actionable insights.

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research.

This book presents an overview of operations research and systems engineering and takes a look into both fields on content, histories, contributions, and future directions so a sound career choice can be made for those who might be deciding on a career path.

This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general.

Extensive, up to date, and readily accessible, this book is a comprehensive reference source on unit roots for students and applied workers.

This book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life.

A guide to the methodologies, typical mathematical notation, and assumptions used in risk assessment calculations Risk Assessment describes the methodologies, the math, and assumptions needed in risk assessment calculations and explores the various statistical analysis procedures that are used for estimating the parameters employed in risk assessment approaches.

Dieses Buch bietet Ihnen eine verständlich vermittelte Ausgangsbasis für die praktische Anwendung datenanalytischer Methoden, die sinnvolle Interpretation von Daten und die Ableitung von Informationen.

All the Tools for Gathering and Analyzing Data and Presenting ResultsReproducible Research with R and RStudio, Second Edition brings together the skills and tools needed for doing and presenting computational research.

This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms.

Given the rapid pace of development in economics and finance, a concise and up-to-date introduction to mathematical methods has become a prerequisite for all graduate students, even those not specializing in quantitative finance.

500 Ways to achieve your best score with this popular study guide for the AP Statistics Exam We've selected these 500 questions to help you study more effectively, use your preparation time wisely, and get your best results.

This book constitutes the refereed proceedings of the 13th European Workshop on Computer Performance Engineering, EPEW 2016, held in Chios, Greece, in October 2016.

A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features.

Developments in multimedia database management have exploded during the past decade.

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing.

This book evolved from several stacks of lecture notes written over a decade and given in classes at slightly varying levels.

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

The first part of this title contained all statistical tests that are relevant for starters on SPSS, and included standard parametric and non-parametric tests for continuous and binary variables, regression methods, trend tests, and reliability and validity assessments of diagnostic tests.

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC's and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup.

Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system.