View All Book Series

BOOK SERIES


Chapman & Hall/CRC Monographs on Statistics and Applied Probability


About the Series

Since its inception in 1960 under the leadership of Sir David R. Cox, the series has established itself as a leading outlet for monographs presenting advances in statistical and applied probability research. With over 150 books published - over 100 still in print - the series has gained a reputation for outstanding quality.

The scope of the series is wide, incorporating developments in statistical methodology of relevance to a range of application areas. The monographs in the series present succinct and authoritative overviews of methodology, often with an emphasis on application through worked examples and software for their implementation. They are written so as to be accessible to graduate students, researchers and practitioners of statistics, as well as quantitative scientists from the many relevant areas of application.

123 Series Titles

Per Page
Sort

Display
Large Covariance and Autocovariance Matrices

Large Covariance and Autocovariance Matrices

1st Edition

Arup Bose, Monika Bhattacharjee
July 03, 2018

Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models. The prerequisites...

Nonparametric Models for Longitudinal Data: With Implementation in R

Nonparametric Models for Longitudinal Data: With Implementation in R

1st Edition

Colin O. Wu, Xin Tian
May 15, 2018

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era...

Multivariate Kernel Smoothing and Its Applications

Multivariate Kernel Smoothing and Its Applications

1st Edition

José E. Chacón, Tarn Duong
May 08, 2018

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the data science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite...

Multistate Models for the Analysis of Life History Data

Multistate Models for the Analysis of Life History Data

1st Edition

Richard J Cook, Jerald F. Lawless
May 04, 2018

Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Special models such as illness-death, competing risks...

Sufficient Dimension Reduction: Methods and Applications with R

Sufficient Dimension Reduction: Methods and Applications with R

1st Edition

Bing Li
May 01, 2018

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of...

Probabilistic Foundations of Statistical Network Analysis

Probabilistic Foundations of Statistical Network Analysis

1st Edition

Harry Crane
April 19, 2018

Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic...

Missing and Modified Data in Nonparametric Estimation: With R Examples

Missing and Modified Data in Nonparametric Estimation: With R Examples

1st Edition

Sam Efromovich
March 12, 2018

This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random,...

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

2nd Edition

Youngjo Lee, John A. Nelder, Yudi Pawitan
August 04, 2017

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical...

Absolute Risk: Methods and Applications in Clinical Management and Public Health

Absolute Risk: Methods and Applications in Clinical Management and Public Health

1st Edition

Ruth M. Pfeiffer, Mitchell H. Gail
July 26, 2017

Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow...

Antedependence Models for Longitudinal Data

Antedependence Models for Longitudinal Data

1st Edition

Dale L. Zimmerman, Vicente A. Núñez-Antón
June 14, 2017

The First Book Dedicated to This Class of Longitudinal Models Although antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models. By gathering results scattered throughout the literature, Antedependence...

Simultaneous Inference in Regression

Simultaneous Inference in Regression

1st Edition

Wei Liu
June 13, 2017

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. Simultaneous Inference in Regression provides a thorough overview of the construction methods and applications of...

Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems

Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems

1st Edition

Jiming Jiang
June 08, 2017

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice....

AJAX loader