Sequential Analysis: Hypothesis Testing and Changepoint Detection

Tartakovsky, Alexander, Nikiforov, Igor, Basseville, Michele

  • 出版商: CRC
  • 出版日期: 2020-12-18
  • 售價: $2,290
  • 貴賓價: 9.5$2,176
  • 語言: 英文
  • 頁數: 603
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0367740044
  • ISBN-13: 9780367740047
  • 相關分類: Data Science機率統計學 Probability-and-statistics
  • 立即出貨 (庫存 < 3)

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商品描述

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.

 

 

商品描述(中文翻譯)

《Sequential Analysis: Hypothesis Testing and Changepoint Detection》系統地發展了序列假設檢定和最快變點檢測的理論。同時,它還描述了可以有效應用理論結果的重要應用。

該書回顧了在決策理論(貝葉斯)和非決策理論(非貝葉斯)背景下的假設檢定和變點檢測的最新成就。作者不僅強調傳統的二元假設,還涉及更困難的多個決策問題。他們討論了簡單假設和更現實的兩個和有限個複合假設的情況。該書主要關注實際的離散時間模型,同時也研究了某些連續時間模型,當兩種情況下可以獲得相似的一般結果時。它詳細介紹了傳統的獨立同分佈和一般的非獨立同分佈隨機模型,包括馬爾可夫、隱馬爾可夫、狀態空間、回歸和自回歸模型。最重要的結果給出了嚴格的證明。

該書由該領域的領先專家撰寫,涵蓋了序列假設檢定和序列最快變點檢測在廣泛的工程和環境領域中的理論發展和應用。它解釋了理論方面如何影響假設檢定和變點檢測問題以及算法設計。

作者簡介

Alexander Tartakovsky, Igor Nikiforov, Michele Basseville

作者簡介(中文翻譯)

亞歷山大·塔爾塔科夫斯基(Alexander Tartakovsky)、伊戈爾·尼基福羅夫(Igor Nikiforov)、米歇爾·巴塞維爾(Michele Basseville)