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.
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach
Large Covariance and Autocovariance Matrices
Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition
Antedependence Models for Longitudinal Data
Simultaneous Inference in Regression
Ross L. Prentice, Shanshan Zhao
June 04, 2019
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of...
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...
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...
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...
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...
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...
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...
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,...
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...
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...
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...
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...