Chapman & Hall/CRC Monographs on Statistics and Applied Probability
About the Book 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.
Please contact us if you have an idea for a book for the series.
Missing and Modified Data in Nonparametric Estimation: With R Examples
1st Edition
By Sam Efromovich
June 30, 2020
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, ...
Models for Dependent Time Series
1st Edition
By Granville Tunnicliffe Wilson, Marco Reale, John Haywood
June 30, 2020
Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and ...
Multi-State Survival Models for Interval-Censored Data
1st Edition
By Ardo van den Hout
June 30, 2020
Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book ...
Multistate Models for the Analysis of Life History Data
1st Edition
By Richard J Cook, Jerald F. Lawless
June 30, 2020
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...
Multivariate Kernel Smoothing and Its Applications
1st Edition
By José E. Chacón, Tarn Duong
June 30, 2020
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 ...
Nonparametric Models for Longitudinal Data: With Implementation in R
1st Edition
By Colin O. Wu, Xin Tian
June 30, 2020
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 ...
State-Space Methods for Time Series Analysis: Theory, Applications and Software
1st Edition
By Jose Casals, Alfredo Garcia-Hiernaux, Miguel Jerez, Sonia Sotoca, A. Alexandre Trindade
June 30, 2020
The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, ...
Analysis of Infectious Disease Data
1st Edition
By N.G. Becker
December 03, 2019
The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen developed only recently, and for those based on particularlymodern mathematics, details of the computation are carefullyillustrated. Interpretation is ...
Analysis of Quantal Response Data
1st Edition
By Byron J.T. Morgan
December 03, 2019
This book takes the standard methods as the starting point, and then describes a wide range of relatively new approaches and procedures designed to deal with more complicated data and experiments - including much recent research in the area. Throughout mention is given to the computing ...
Predictive Inference
1st Edition
By Seymour Geisser
December 03, 2019
The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference. While the book discusses a variety of approaches to prediction ...
Nonlinear Time Series: Semiparametric and Nonparametric Methods
1st Edition
By Jiti Gao
October 18, 2019
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve ...
Multivariate Dependencies: Models, Analysis and Interpretation
1st Edition
By D.R. Cox, Nanny Wermuth
October 17, 2019
Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields including the social and medical sciences. This book sets out both the general concepts and the more technical statistical issues involved in analysis ...