Catalogue


Stage-wise adaptive designs [electronic resource] /
Shelemyahu Zacks.
imprint
Hoboken, N.J. : John Wiley, c2009.
description
xiv, 386 p. : ill. ; 25 cm.
ISBN
9780470050958 (cloth)
format(s)
Book
More Details
imprint
Hoboken, N.J. : John Wiley, c2009.
isbn
9780470050958 (cloth)
restrictions
Licensed for access by U. of T. users.
contents note
Synopsis -- Multi-stage and sequential estimation -- Adaptive designs for generalized linear models -- Adaptive methods for sampling from finite populations -- Adaptive estimation of the size of a finite population -- Adaptive prediction and forecasting in time series analysis -- Adaptive search of an MTD in cancer phase I clinical trials -- Adaptive and sequential procedures in clinical trials, phases II and III -- Sequential allocation of resources -- Sequential detection of change-points -- Sequential methods in industrial testing.
catalogue key
8071470
 
Includes bibliographical references (p. 313-335) and indexes.
A Look Inside
About the Author
Author Affiliation
Shelemyahu Zacks, PhD, is Professor of Statistics in the Department of Mathematical Sciences at Binghamton University. He has published several books and over 170 journal articles in the areas of design and analysis of experiments, statistical control of stochastic processes, statistical decision theory, statistical methods in logistics, and sampling from finite populations. Dr. Zacks is a Fellow of the American Statistical Association, Institute of Mathematical Sciences, and American Association for the Advancement of Sciences.
Excerpts
Flap Copy
Stage-Wise Adaptive DesignsAn expert introduction to stage-wise adaptive designs in all areas of statisticsStage-Wise Adaptive Designs presents the theory and methodology of stage-wise adaptive design across various areas of study within the field of statistics, from sampling surveys and time series analysis to generalized linear models and decision theory. Providing the necessary background material along with illustrative S-PLUS functions, this book serves as a valuable introduction to the problems of adaptive designs.The author begins with a cohesive introduction to the subject and goes on to concentrate on generalized linear models, followed by stage-wise sampling procedures in sampling surveys. Adaptive forecasting in the area of time series analysis is presented in detail, and two chapters are devoted to applications in clinical trials. Bandits problems are also given a thorough treatment along with sequential detection of change-points, sequential applications in industrial statistics, and software reliability.S-Plus functions are available to accompany particular computations, and all examples can be worked out using R, which is available on the book's related FTP site. In addition, a detailed appendix outlines the use of these software functions, while an extensive bibliography directs readers to further research on the subject matter.Assuming only a basic background in statistical topics, Stage-Wise Adaptive Designs is an excellent supplement to statistics courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and practitioners in the fields of statistics and biostatistics.
Reviews
Review Quotes
"Covering a broad range of material, this book may serve well as a reference source for adaptive approaches in the design of experiments." (Mathematical Reviews, 2011)
To find out how to look for other reviews, please see our guides to finding book reviews in the Sciences or Social Sciences and Humanities.
Summaries
Main Description
Stage-Wise Adaptive Designs presents the theory and methodology of stage-wise adaptive design across various areas of study within the field of statistics, from sampling surveys and time series analysis to generalized linear models and decision theory. Providing the necessary background material along with illustrative S-PLUS functions, this book serves as a valuable introduction to the problems of adaptive designs.
Main Description
Adaptive methods can be found in all fields of statistics. Written by an eminent statistician who has a strong working knowledge of all the key areas in statistics that make use of adaptive designs, this book presents the theory and methodology of stagewise adaptive designs in all applicable fields of statistics. The book includes such novel content as Bayesian dynamic adaptive techniques (for finance), adaptive decision making and sequential analysis (for survey sampling), and adaptive filtering (for engineering). This extensively class-tested text is ideal for researchers, practitioners, and students.
Long Description
An expert introduction to stage-wise adaptive designs in all areas of statisticsStage-Wise Adaptive Designs presents the theory and methodology of stage-wise adaptive design across various areas of study within the field of statistics, from sampling surveys and time series analysis to generalized linear models and decision theory. Providing the necessary background material along with illustrative S-PLUS functions, this book serves as a valuable introduction to the problems of adaptive designs.The author begins with a cohesive introduction to the subject and goes on to concentrate on generalized linear models, followed by stage-wise sampling procedures in sampling surveys. Adaptive forecasting in the area of time series analysis is presented in detail, and two chapters are devoted to applications in clinical trials. Bandits problems are also given a thorough treatment along with sequential detection of change-points, sequential applications in industrial statistics, and software reliability.S-Plus functions are available to accompany particular computations, and all examples can be worked out using R, which is available on the book's related FTP site. In addition, a detailed appendix outlines the use of these software functions, while an extensive bibliography directs readers to further research on the subject matter.Assuming only a basic background in statistical topics, Stage-Wise Adaptive Designs is an excellent supplement to statistics courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and practitioners in the fields of statistics and biostatistics.
Main Description
An expert introduction to stage-wise adaptive designs in all areas of statistics Stage-Wise Adaptive Designs presents the theory and methodology of stage-wise adaptive design across various areas of study within the field of statistics, from sampling surveys and time series analysis to generalized linear models and decision theory. Providing the necessary background material along with illustrative S-PLUS functions, this book serves as a valuable introduction to the problems of adaptive designs. The author begins with a cohesive introduction to the subject and goes on to concentrate on generalized linear models, followed by stage-wise sampling procedures in sampling surveys. Adaptive forecasting in the area of time series analysis is presented in detail, and two chapters are devoted to applications in clinical trials. Bandits problems are also given a thorough treatment along with sequential detection of change-points, sequential applications in industrial statistics, and software reliability. S-Plus functions are available to accompany particular computations, and all examples can be worked out using R, which is available on the book's related FTP site. In addition, a detailed appendix outlines the use of these software functions, while an extensive bibliography directs readers to further research on the subject matter. Assuming only a basic background in statistical topics, Stage-Wise Adaptive Designs is an excellent supplement to statistics courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and practitioners in the fields of statistics and biostatistics.
Table of Contents
Prefacep. xiii
Synopsisp. 1
Multistage and Sequential Estimationp. 1
Adaptive Designs for Generalized Linear Modelsp. 3
Adaptive Methods for Sampling from Finite Populationsp. 5
Adaptive Prediction and Forecasting in Time Series Analysisp. 6
Adaptive Search of an MTD in Cancer Phase I Clinical Trialsp. 7
Adaptive and Sequential Procedures in Phase III Clinical Trialsp. 9
Sequential Allocation of Resourcesp. 10
Sequential Detection of Change Pointsp. 12
Sequential Methods in Industrial Testing, Reliability, and Design of Experimentsp. 13
Multistage and Sequential Estimationp. 15
Stein's Two-Stage Procedurep. 15
Modifications to Attain Asymptotic Efficiencyp. 18
Two-Stage Sampling from Exponential Distributionsp. 20
Fixed-Width Confidence Interval for the Location Parameter of an Exponential Distributionp. 20
Two-Stage Sampling for a Bounded Risk Point Estimation of the Exponential Parameterp. 24
Sequential Fixed-Width Interval Estimationp. 34
Distributions of Stopping Variables of Sequential Samplingp. 37
General Theoryp. 38
Characteristics of Ray's Procedurep. 40
Risk of Some Sequential Point Estimatorsp. 41
Sequential Fixed-Width Intervals for the Log-Odds in Bernoulli Trialsp. 42
Problemp. 42
Distribution of N (¿)p. 43
Functionals of ¿&hat;N(¿)p. 47
Bayesian Sequential Estimationp. 49
General Theoryp. 49
Estimating the Scale Parameter of the Exponential Distributionp. 51
Adaptive Designs for Generalized Linear Modelsp. 55
Exponential Examplep. 55
Adaptive Designs for the Fisher Informationp. 57
Adaptive Bayesian Designsp. 63
Adaptive Designs for Inverse Regressionp. 66
Non-Bayesian Adaptive Designsp. 66
Bayesian Adaptive Designs, ¿ Knownp. 71
Stochastic Approximationp. 73
Adaptive Methods for Sampling from Finite Populationsp. 75
Basic Theoryp. 75
Design Approachp. 76
Modeling Approachp. 79
Two-Stage and Sequential Estimation of the Population Meanp. 81
Design Approach: SRSWRp. 81
Design Approach: SRSWORp. 84
Modeling Approachp. 86
Adaptive Allocation of Stratified SRSp. 86
Basic Theoryp. 87
Two-Stage Procedure for a Fixed-Width Interval Estimation of &Ybar;n Under Stratified Samplingp. 88
Adaptive Search for Special Unitsp. 91
Adaptive Estimation of the Size of a Finite Populationp. 92
Applications in Software Reliabilityp. 96
Sequential Stopping for Time Domain Modelsp. 96
Sequential Stopping for Data Domain Modelsp. 98
Sampling Inspection Schemesp. 100
Two-Stage Sampling for Attributesp. 100
Sequential Sampling for Attributesp. 102
Dynamic Bayesian Predictionp. 103
Adaptive Prediction and Forecasting in Time Series Analysisp. 107
Basic Tools of Time Series Analysisp. 107
Linear Predictors for Covariance Stationary T.S.p. 113
Optimal Linear Predictorsp. 113
Minimal PMSE Predictors for AR(p) T.S.p. 117
Prediction with Unknown Covariance Structurep. 119
ARIMA Forecastingp. 121
Quadratic LSE Predictors for Nonstationary T.S.p. 124
Moving Average Predictors for Nonstationary T.S.p. 128
Linear MAS Predictorsp. 130
Predictors for General Trends with Exponential Discountingp. 132
Recursive Computations with Shifted Originp. 133
Linear Trendp. 136
Linear Trend with Cyclical Componentsp. 137
Dynamic Linear Modelsp. 141
Recursive Computations for the Normal Random Walk DLM, Constant Variancesp. 143
Incorporating External Informationp. 146
General DLM with Applicationsp. 147
DLM for ARMA(p,q) T.S.p. 153
Asymptotic Behavior of DLMp. 157
Linear Control of DLMp. 163
Deterministic Linear Controlp. 163
Stochastic Linear Controlp. 166
Adaptive Search of an MTD in Cancer Phase I Clinical Trialsp. 171
Up-and-Down Adaptive Designsp. 171
Bayesian Adaptive Search: The Continuous Reassessment Methodp. 177
Efficient Dose Escalation with Overdose Controlp. 179
Patient-Specific Dosingp. 181
Toxicity versus Efficacyp. 182
Adaptive and Sequential Procedures in Clinical Trials, Phases II and IIIp. 185
Randomization in Clinical Trialsp. 185
Adaptive Randomization Proceduresp. 187
Random Allocation Rulep. 187
Truncated Binomial Designp. 189
Efron's Biased Coin Designp. 190
Wei's Urn Designp. 192
Response Adaptive Designsp. 192
Fixed-Width Sequential Estimation of the Success Probability in Bernoulli Trialsp. 193
Sequential Procedure for Estimating the Probability of Success in Bernoulli Trialsp. 197
Sequential Comparison of Success Probabilitiesp. 198
Group Sequential Methodsp. 200
Dynamic Determination of Stage-Wise Sample Sizep. 205
Truncated Three-Stage Procedure for Power (TTSP)p. 205
Bartoff-Lai GLR Procedurep. 208
Sequential Allocation of Resourcesp. 211
Bernoulli Banditsp. 211
Gittins Dynamic Allocation Indicesp. 216
Sequential Allocations in Clinical Trialsp. 218
Bernoulli Bandits with Change Pointp. 221
Introductionp. 221
Optimizing the Final Cyclep. 222
Surveillance Cyclep. 224
Multiple Surveillance Cyclesp. 230
Sequential Designs for Estimating the Common Mean of Two Normal Distributions: One Variance Knownp. 233
Sequential Detection of Change Pointsp. 237
Bayesian Detection When the Distributions Before and After the Change Are Knownp. 237
Problemp. 237
Bayesian Frameworkp. 238
Application in System Reliabilityp. 241
Optimal Stopping for Detecting a Change Point in the intensity of a Poisson Processp. 243
Bayesian Detection When the Distributions Before and After the Change Are Unknownp. 245
Bayesian Frameworkp. 246
Optimal Stopping Rulesp. 247
Detecting a Change in the Success Probabilities of Binomial Trials: An Examplep. 248
CUSUM Procedures for Sequential Detectionp. 250
Structure of CUSUM Proceduresp. 250
Asymptotic Minimaxity of CUSUM Proceduresp. 251
Exact Distribution of Stopping Variables in CUSUM Proceduresp. 253
Tracking Algorithms for Processes with Change Pointsp. 258
General Commentsp. 258
Tracking a Process with Change Pointsp. 259
Recursive Nonlinear Estimation with Moving Windowsp. 260
Specific Casesp. 263
Case Studiesp. 269
Recursive Estimation with Change Pointsp. 272
Reaction of Recursive Estimators to Change Pointsp. 272
Recursive Estimation with the Kalman Filterp. 276
Detecting Change Points in Recursive Estimationp. 278
Adjustment of the Kalman Filter for Change Pointsp. 279
Special Casep. 282
Additional Theoretical Contributionsp. 283
Sequential Methods In Industrial Testingp. 285
Sequential Testing (SPRT)p. 285
Wald Sequential Probability Ratio Testp. 286
Exact Distributions of N in the Exponential Casep. 294
Characteristics of Sequential Procedures in Reliability Estimation and Testingp. 298
Reliability Estimationp. 299
Reliability Testingp. 302
Total Operating Time of Repairable Systemp. 304
Some Comments on Sequential Design of Experimentsp. 305
Sequential Testing of Software Reliabilityp. 308
Complete Bayesian Modelp. 309
Empirical Bayes: Adaptive Approach When ¿ and ¿ Are Unknownp. 310
Bibliographyp. 313
Appendix: SPLUS/R Programsp. 336
Author Indexp. 375
Topic Indexp. 382
Table of Contents provided by Ingram. All Rights Reserved.

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