Applied Sequential Methodologies: Real-World Examples with Data Analysis (STATISTICS, A SERIES OF TEXTBOOKS AND MONOGRAPHS)

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.

Nitis Mukhopadhyay, Sujay Datta, Saibal Chattopadhyay