Chapman & Hall/CRC Monographs on Statistics & Applied Probability

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1 - 12 of 119 Series Titles

Handbook of Approximate Bayesian Computation

Forthcoming

Scott A. Sisson, Yanan Fan, Mark Beaumont

January 26, 2016

Approximate Bayesian Computation (ABC) methods, also known as "likelihood-free" inference methods, can be used to solve very complex ("computationally intractable") problems. A huge amount of research has been conducted in this area over the last decade and a varied suite of algorithms, models, 

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition

Forthcoming

Walter Zucchini, Iain L. MacDonald, Roland Langrock

January 26, 2016


Mixed Models

Forthcoming

Geert Verbeke, Geert Molenberghs

January 15, 2016


Structural Nonparametric Models for the Analysis of Longitudinal Data

Forthcoming

Colin O. Wu, Xin Tian

January 15, 2016

This book covers the recent advancement of statistical methods for the analysis of longitudinal data. Real datasets from four large NIH-supported longitudinal clinical trials and epidemiological studies illustrate the practical applications of the statistical methods. This book focuses on the 

Change-point Methodology and Applications

Forthcoming

Tze Leung Lai, Haipeng Xing

January 15, 2016


Managing Uncertainty in Complex Models

Forthcoming

Jeremy E. Oakley

December 26, 2015

This book describes statistical methods for analyzing uncertainty in complex mathematical or computational models of physical systems. Such models are widely used in science and engineering—for example, climate models or cost-effectiveness models in health economics—and almost always have 

Absolute or Crude Risk: Applications in Disease Prevention

Forthcoming

Mitchell H. Gail, Ruth Pfeiffer

December 15, 2015

Absolute risk is the probability of developing a specific disease over a specified time interval in the presence of competing causes of mortality. Although absolute risk is arguably more relevant to clinical decision making than "pure" risk, the development of appropriate statistical methods for 

Martingale Methods in Statistics

Forthcoming

Yoichi Nishiyama

December 15, 2015

This gives a comprehensive introduction to the (standard) statistical analysis based on the theory of martingales and develops entropy methods in order to treat dependent data in the framework of martingales. The author starts a summary of the martingale theory, and then proceeds to give full 

Propensity Score Modeling and Adjustment Procedures

Forthcoming

David Stephens

December 15, 2015

This book provides a good balance of propensity score modeling theory (particularly semiparametric methods) and applications through worked examples and software, including R and Stata code. Key topics covered include longitudinal data, survival data, survey sampling, model selection, and Bayesian 

Multi-State Survival Models for Interval-Censored Data

Forthcoming

Ardo van den Hout

November 30, 2015

Multi-state models describe stochastic processes that consist of transitions between states over time, such as the three-state illness-death model. Interval-censored data is extremely common as the exact time of transition from one state to another is unknown—only an interval of time is known. This 

Perfect Simulation

Forthcoming

Mark L. Huber

November 15, 2015


Inferential Models: Reasoning with Uncertainty

Forthcoming

Chuanhai Liu, Ryan Martin

September 26, 2015

This book delves into the authors’ work toward deeper understanding of statistical inference in terms of reasoning with uncertainty and meaningfulness of probabilistic inferential output. Focusing on a valid, prior-free probabilistic inferential framework called inferential models, the authors 

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