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, ...
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 ...
Time Series Models: In econometrics, finance and other fields
1st Edition
Edited
By D.R. Cox, D.V. Hinkley, O.E. Barndorff-Nielsen
October 17, 2019
The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints ...
Classification
2nd Edition
By A.D. Gordon
October 07, 2019
As the amount of information recorded and stored electronically grows ever larger, it becomes increasingly useful, if not essential, to develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification does just ...
Accelerated Life Models: Modeling and Statistical Analysis
1st Edition
By Vilijandas Bagdonavicius, Mikhail Nikulin
September 05, 2019
The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. In a unified, systematic presentation, this monograph fully details those models and explores areas of accelerated life testing usually only touched upon...