An advanced discussion of linear models with mixed or random effects.

In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for...

This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures. This edition features some procedures that have withstood the test of time and are now used by many practitioners, such as the Fisher Exact Test for two-by-two contingency tables, the Mantel-Haenszel Test for combining several contingency tables, the Kaplan-Meier estimates of the survival curve, the Jonckheere-Terpstra Test and the Page Test for ordered alternatives, and a discussion of the bootstrap method.

This text covers the essentials of stochastic dynamic programming (also known as stochastic optimal control, Markov decision processes, or Markov decision chains) with a specific focus on the application of queueing theory. The text integrates both theory and computation in its discussion of stochastic dynamic programming. The theory of optimization criterion is first developed and proven before giving the computational methods to determine the numerical policies of the theory. Focusing on queueing systems allows for an in-depth exploration of the application of the outlined principles

This text covers modelling and simulation of discrete-event systems (DES). Examples include computer communications networks, flexible manufacturing systems, PERT (project evaluation and review techniques) networks and flow networks including queuing systems. These systems are typically driven by the occurrence of discrete-events and their changes in time. In view of the complex interactions among such discrete events, the corresponding systems are often studied via stochastic simulation.

This applications-orientated book discusses the major updated methods in the analysis of survival data. It covers both parametric and nonparametric methods, with emphasis on the latter's more recent developments applied to health research.

A comprehensive framework for both reduction of nonresponse and postsurvey adjustment for nonresponse

This book provides guidance and support for survey statisticians who need to develop models for postsurvey adjustment for nonresponse, and for survey designers and practitioners attempting to reduce unit nonresponse in household interview surveys. It presents the results of an eight-year research program that has assembled an unprecedented data set on respondents and nonrespondents from several major household surveys in the United States.

Within a comprehensive...

This text is about ideas for the graphical analysis of regression data. A statistical context for regression and regression graphics is emphasized. This new context is intended to blend with, rather than replace, most traditional paradigms for regression analysis. Residuals are an important part of graphics for regression analysis, and they play key roles in this book. But they are not singled out for special study; rather, they occur throughout the volume in different roles depending on the context.

Expert practical and theoretical coverage of runs and scans
This volume presents both theoretical and applied aspects of runs and scans, and illustrates their important role in reliability analysis through various applications from science and engineering. Runs and Scans with Applications presents new and exciting content in a systematic and cohesive way in a single comprehensive volume, complete with relevant approximations and explanations of some limit theorems.
The authors provide detailed discussions of both classical and current problems, such as:
* Sooner and later...

New statistical methods and future directions of research in time series

A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building...

• Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns.
• Introduces the martingale and counting process formulation swil lbe in a new chapter.
• Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations.
• Presents new examples and applications of data analysis.