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Chapman & Hall/CRC Texts in Statistical Science


105 Series Titles

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Stochastic Processes: An Introduction, Third Edition

Stochastic Processes: An Introduction, Third Edition

Forthcoming

Peter Watts Jones, Peter Smith
July 25, 2017

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability...

Introduction to Statistical Methods for Financial Models

Introduction to Statistical Methods for Financial Models

Forthcoming

Thomas A Severini
July 14, 2017

This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4...

Statistical Regression and Classification: From Linear Models to Machine Learning

Statistical Regression and Classification: From Linear Models to Machine Learning

Forthcoming

Norman Matloff
June 28, 2017

Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at the traditional statistical regression course, presenting a contemporary treatment in line with today's applications and users. The text takes a modern look at regression: * A thorough...

Introduction to Functional Data Analysis

Introduction to Functional Data Analysis

Forthcoming

Piotr Kokoszka, Matthew Reimherr
May 29, 2017

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 methodology and the required mathematical framework....

Generalized Additive Models: An Introduction with R, Second Edition

Generalized Additive Models: An Introduction with R, Second Edition

Forthcoming

Simon N. Wood
April 21, 2017

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary...

Modern Data Science with R

Modern Data Science with R

Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 02, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical...

Stochastic Processes: From Applications to Theory

Stochastic Processes: From Applications to Theory

Pierre Del Moral, Spiridon Penev
December 19, 2016

Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the...

Modeling and Analysis of Stochastic Systems, Third Edition

Modeling and Analysis of Stochastic Systems, Third Edition

Vidyadhar G. Kulkarni
October 07, 2016

Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition,...

Pragmatics of Uncertainty

Pragmatics of Uncertainty

Joseph B. Kadane
September 27, 2016

A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working....

Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition

Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition

Julian J. Faraway
March 24, 2016

Start Analyzing a Wide Range of Problems Since the publication of the bestselling, highly recommended first edition, R has considerably expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric...

Essentials of Probability Theory for Statisticians

Essentials of Probability Theory for Statisticians

Michael A. Proschan, Pamela A. Shaw
March 15, 2016

Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics. It presents classical probability theory motivated with illustrative examples in biostatistics, such as...

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition

Ronald Christensen
December 22, 2015

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 linear model for the data. The book carefully...

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