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Chapman & Hall/CRC Texts in Statistical Science


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Linear Models and the Relevant Distributions and Matrix Algebra

Linear Models and the Relevant Distributions and Matrix Algebra

Forthcoming

David A. Harville
February 22, 2018

Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models...

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference

Forthcoming

Athanasios Christou Micheas
January 29, 2018

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks....

Stochastic Processes: An Introduction, Third Edition

Stochastic Processes: An Introduction, Third Edition

Peter Watts Jones, Peter Smith
October 16, 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 Functional Data Analysis

Introduction to Functional Data Analysis

Piotr Kokoszka, Matthew Reimherr
August 09, 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....

Statistical Regression and Classification: From Linear Models to Machine Learning

Statistical Regression and Classification: From Linear Models to Machine Learning

Norman Matloff
August 01, 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 Statistical Methods for Financial Models

Introduction to Statistical Methods for Financial Models

Thomas A Severini
July 12, 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...

Design of Experiments: An Introduction Based on Linear Models

Design of Experiments: An Introduction Based on Linear Models

Max Morris
May 31, 2017

Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for...

Generalized Additive Models: An Introduction with R, Second Edition

Generalized Additive Models: An Introduction with R, Second Edition

Simon N. Wood
May 30, 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...

Logistic Regression Models

Logistic Regression Models

Joseph M. Hilbe
May 25, 2017

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The...

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...

Multivariate Survival Analysis and Competing Risks

Multivariate Survival Analysis and Competing Risks

Martin J. Crowder
November 16, 2016

Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions...

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