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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.

Please contact us if you have an idea for a book for the series.

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Dynamic Treatment Regime: Statistical Methods for Precision Medicine

Dynamic Treatment Regime: Statistical Methods for Precision Medicine

1st Edition

Forthcoming

Anastasios A. Tsiatis, Marie Davidian, Shannon T. Holloway, Eric B. Laber
December 20, 2019

Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a comprehensive introduction to statistical methodology for evaluation and discovery of dynamic treatment regimes from data. Methodological developments in this area are scattered across a vast, diverse literature,...

Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules

Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules

1st Edition

Forthcoming

Alexander Tartakovsky
December 05, 2019

How can major corporations and governments more quickly and accurately detect and address cyberattacks on their networks? How can local authorities improve early detection and prevention of epidemics? How can researchers improve the identification and classification of space objects in difficult (...

Nonlinear Time Series: Semiparametric and Nonparametric Methods

Nonlinear Time Series: Semiparametric and Nonparametric Methods

1st Edition

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

Multivariate Dependencies: Models, Analysis and Interpretation

1st Edition

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...

Classification

Classification

2nd Edition

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...

Subjective Probability Models for Lifetimes

Subjective Probability Models for Lifetimes

1st Edition

Fabio Spizzichino
September 05, 2019

Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some fundamental concepts be...

Components of Variance

Components of Variance

1st Edition

D.R. Cox, P.J. Solomon
September 05, 2019

Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing. Only in very simple situations can such variations be represented effectively by...

Subset Selection in Regression

Subset Selection in Regression

2nd Edition

Alan Miller
September 05, 2019

Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition...

Accelerated Life Models: Modeling and Statistical Analysis

Accelerated Life Models: Modeling and Statistical Analysis

1st Edition

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...

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach

1st Edition

Ross L. Prentice, Shanshan Zhao
May 16, 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...

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...

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