Missing Data in Longitudinal Studies Strategies for Bayesian Modeling and Sensitivity Analysis
Stereology for Statisticians
Diagnostic Checks in Time Series
Statistics in the 21st Century
The Theory of the Design of Experiments
By Michael J. Daniels, Joseph W. Hogan
March 11, 2008
Drawing from the authors’ own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To ...
By Raymond J. Carroll, David Ruppert, Leonard A. Stefanski, Ciprian M. Crainiceanu
June 21, 2006
It’s been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, ...
By Havard Rue, Leonhard Held
February 18, 2005
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the ...
By Adrian Baddeley, Eva B. Vedel Jensen
November 29, 2004
Setting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistical issues to clients, draw attention to common methodological errors, and provide references to ...
By Wai Keung Li
December 29, 2003
Diagnostic checking is an important step in the modeling process. But while the literature on diagnostic checks is quite extensive and many texts on time series modeling are available, it still remains difficult to find a book that adequately covers methods for performing diagnostic ...
By Jesper Moller, Rasmus Plenge Waagepetersen
September 25, 2003
Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods...
By Barbel Finkenstadt, Holger Rootzen
July 28, 2003
Because of its potential to ...predict the unpredictable,... extreme value theory (EVT) and methodology is currently receiving a great deal of attention from statistical and mathematical researchers. This book brings together world-recognized authorities in their respective fields to provide ...
By Martin A. Tanner, Martin T. Wells
July 09, 2001
This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods of statistics....
By Art B. Owen
May 18, 2001
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it...
By Nina Golyandina, Vladimir Nekrutkin, Anatoly A Zhigljavsky
January 23, 2001
Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series ...
By Giovanni Pistone, Eva Riccomagno, Henry P. Wynn
December 21, 2000
Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Gröbner bases and a thorough description of their applications to experimental design...
By D.R. Cox, Nancy Reid
June 06, 2000
Why study the theory of experiment design? Although it can be useful to know about special designs for specific purposes, experience suggests that a particular design can rarely be used directly. It needs adaptation to accommodate the circumstances of the experiment. Successful designs depend upon ...