Alexander Tartakovsky, Igor Nikiforov, Michele Basseville

Sequential Analysis

Hypothesis Testing and Changepoint Detection

• Gebundenes Buch

Produktbeschreibung

This book covers the theoretical developments and applications of sequential hypothesis testing and sequential quickest changepoint detection in a wide range of engineering and environmental domains. It reviews recent accomplishments in hypothesis testing and changepoint detection both in decision-theoretic (Bayesian) and non-decision-theoretic (non-Bayesian) contexts. The authors not only emphasize traditional binary hypotheses but also substantially more difficult multiple decision problems. They treat conventional i.i.d. and general non-i.i.d. stochastic models in detail, including Markov, hidden Markov, state-space, regression, and autoregression models.

Produktdetails

• Verlag: CRC Press
• Seitenzahl: 604
• Erscheinungstermin: 1. August 2014
• Englisch
• Abmessung: 261mm x 177mm x 43mm
• Gewicht: 1226g
• ISBN-13: 9781439838204
• ISBN-10: 1439838208
• Artikelnr.: 34762603

Autorenporträt

Alexander Tartakovsky, Igor Nikiforov, Michele Basseville

Inhaltsangabe

Motivations for the sequential approach. Background on probability and statistics. Sequential Hypothesis Testing: Sequential hypothesis testing
Two simple hypotheses. Sequential hypothesis testing
Multiple simple hypotheses. Sequential hypothesis testing
Composite hypotheses. Change
Point Detection: Statistical models with changes
Problem formulations and optimality criteria. Sequential change
point detection
Bayesian approach. Sequential change
point detection
Non
Bayesian approaches. Multichart change
point detection procedures for composite hypotheses and multipopulation models. Sequential change
point detection and isolation. Applications: Selected applications.