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Applied Sequential Methodologies offers a technically precise yet clear presentation of modern sequential methodologies having immediate applicability to practical problems in the real world. It brings crucial sequential approaches up to speed with recent theoretical gains and demonstrates their utility in solving real-life problems associated with change-point detection in multichannel and distributed systems, best-component selection for multivariate distributions, and multistate processes. The chapters contributed by international authorities contain valuable methods for data mining, agriculture science, genetics, computer simulation, finance, clinical trials, and more.
List of contents
Passive Acoustic Detection of Marine Mammals Using Page's Test. Two-Stage Procedures for Selecting the Best Component of a Multivariate Distribution. Sequential Randomization Tests. Sequential Methods for Multistate Processes. Sequential Adaptive Designs for Clinical Trials with Longitudinal Responses. Sequential Approaches to Data Mining. Approximations and Bounds for Moving Sums of Discrete Random Variables. Estimation of the Slope in a Measurement-Error Model. Kernel Density Estimation of Wool Fiber Diameter. Financial Applications of Sequential Nonparametric Curve Estimation.
About the author
Nitis Mukhopadhyay, Sujay Datta, Saibal Chattopadhyay
Summary
A technically precise yet clear presentation of modern sequential methodologies having immediate applications to practical problems in the real world, Applied Sequential Methodologies communicates invaluable techniques for data mining, agricultural science, genetics, computer simulation, finance, clinical trials, sonar signal detection, randomization, multiple comparisons, psychology, tracking, surveillance, and numerous additional areas of application.
Includes more than 500 references, 165 figures and tables, and over 25 pages of subject and author indexes.
Applied Sequential Methodologies brings the crucial nature of sequential approaches up to speed with recent theoretical gains, demonstrating their utility for solving real-life problems associated with
Change-point detection in multichannel and distributed systems
Best component selection for multivariate distributions
Multistate processes
Approximations for moving sums of discrete random variables
Interim and terminal analyses of clinical trials
Adaptive designs for longitudinal clinical trials
Slope estimation in measurement-error models
Tests for randomization and target tracking
Appropriate count of simulation runs
Stock price models
Orders of genes
Size and power control in multiple comparisons
Authored by 33 leading scientists, this volume will greatly benefit sequential analysts, data analysts, applied statisticians, biometricians, clinical trialists, and upper-level undergraduate and graduate students in these disciplines.
