Probability & Statistics

Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this...

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probability laws, central and non-central limit theorems for...

Now in its third edition, this companion volume to Ronald Christensen's Plane Answers to Complex Questions uses three fundamental concepts from standard linear model theory-best linear prediction, projections, and Mahalanobis distance- to extend standard...

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned...

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear...

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. Accessible to practicing fisheries...

The book deals with a powerful and convenient approach to a great variety of types of problems of the recursive monte-carlo or stochastic approximation type. Such recu- sive algorithms occur frequently in stochastic and adaptive control and optimization...

Functional Gaussian Approximation for Dependent Structures develops and analyses mathematical models for phenomena that evolve in time and influence each another. It provides a better understanding of the structure and asymptotic behaviour of stochastic...

This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important...

Experimental data can often be associated with or indexed by certain symmetrically interesting structures or sets of labels that appear, for example, in the study of short symbolic sequences in molecular biology, in preference or voting data, in...

There are already several excellent books on Malliavin calculus. However, most of them deal only with the theory of Malliavin calculus for Brownian motion, with [35] as an honorable exception. Moreover, most of them discuss only the applicationto...

Praise for the First Edition "This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic...I believe that it has the potential to turn small area estimation...into a larger area...

This book provides a comprehensive treatment of the logic behind hypothesis testing. Readers will learn to understand statistical hypothesis testing and how to interpret P-values under a variety of conditions including a single hypothesis test, a...

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a...

Random process analysis (RPA) is used as a mathematical model in physics, chemistry, biology, computer science, information theory, economics, environmental science, and many other disciplines. Over time, it has become more and more important for the...

The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by...

Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches,...

In modern society, we are ever more aware of the environmentalissues we face, whether these relate to global warming, depletionof rivers and oceans, despoliation of forests, pollution of land,poor air quality, environmental health issues, etc. At the...

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in...

Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the...

One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to...

Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of experiments, and optimization. Experimentation through...

Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers...

See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the...

Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and...

AP Teachers' #1 Choice!Ready to succeed in your AP course and ace your exam? Our 5 Steps to a 5 guides explain the tough stuff, offer tons of practice and explanations, and help you make the most efficient use of your study time. 5 Steps to a 5: AP...

Percolation theory was initiated some fifty years ago as a mathematical framework for the study of random physical processes such as flow through a disordered porous medium. It has proved to be a remarkably rich theory, with applications beyond natural...

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Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780486468990Author Sergio AlbeverioFormat PaperbackPage Count 528Imprint Dover Publications Inc.Publisher Dover Publications Inc.Weight(grams)...

A collection of stimulating probability puzzles from bestselling math writer Paul NahinWhat are the chances of a game-show contestant finding a chicken in a box? Is the Hanukkah dreidel a fair game? Will you be alive ten years from now? These are some of...

This book uses a model we have developed for teaching mathematical statistics through in depth case studies. Traditional statistics texts have many small numer ical examples in each chapter to illustrate a topic in statistical theory. Here, we instead...

Designed for anyone who needs a comprehensive introduction to the principles of statistical methods and their applications, this text is written in a practical, non-threatening style. Step-by-step worked examples are used to illustrate the use of...

This book arose out of two graduate courses that the authors have taught duringthepastseveralyears;the?rstonebeingonmeasuretheoryfollowed by the second one on advanced probability theory. The traditional approach to a ?rst course in measure theory, such...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781319383688Author David S. MooreFormat PaperbackImprint W.H.Freeman & Co LtdPublisher Macmillan Learning

Praise for the first edition:"One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff-inferential statistics. The author manages to do this very quickly....if one were...

Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying...

This book, an introduction to statistical inference, has evolved from material used in a first-year undergraduate statistics course at the University of Aberdeen. It relates to the collection of data to answer specific questions and to the interpretation...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780486481586Author Robert B. ASHFormat HardbackPage Count 128Imprint Dover Publications Inc.Publisher Dover Publications Inc.Weight(grams)...

Statistical and mathematical models are defined by parameters that describe different characteristics of those models. Ideally it would be possible to find parameter estimates for every parameter in that model, but, in some cases, this is not possible...

THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA-NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of...