Sequential Analysis
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Sequential Analysis
The first to solve the general problem of sequential tests of statistical hypotheses, the author of this text explains his revolutionary theory of the sequential probability ratio test and its applications. 1947 edition.
Sequential Analysis
Author: John Mordechai Gottman
language: en
Publisher: Cambridge University Press
Release Date: 1990-04-27
In the observational study of social systems, the major conceptual innovation of the last century was General Systems Theory. Yet the General Systems Theory conceptions of interacting social systems were doomed to remain at the prescientific level of metaphor until a set of statistical techniques were developed and applied.
Sequential Analysis
Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently. The book 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 address scenarios with simple hypotheses and more realistic cases of two and finitely many composite hypotheses. The book primarily focuses on practical discrete-time models, with certain continuous-time models also examined when general results can be obtained very similarly in both cases. It treats both conventional i.i.d. and general non-i.i.d. stochastic models in detail, including Markov, hidden Markov, state-space, regression, and autoregression models. Rigorous proofs are given for the most important results. Written by leading authorities in the field, 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 explains how the theoretical aspects influence the hypothesis testing and changepoint detection problems as well as the design of algorithms.