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Sequential Analysis

Sequential Analysis
Author :
Publisher : CRC Press
Total Pages : 600
Release :
ISBN-10 : 9781439838211
ISBN-13 : 1439838216
Rating : 4/5 (11 Downloads)
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Book Synopsis Sequential Analysis by : Alexander Tartakovsky

Download or read book Sequential Analysis written by Alexander Tartakovsky and published by CRC Press. This book was released on 2014-08-27 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 detecti


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Sequential Analysis
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Sequential Analysis

Authors: Alexander Tartakovsky
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Type: BOOK - Published: 2014-08-27 - Publisher: CRC Press

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Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint d
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Bayesian Time Series Models

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Categories: Computers
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The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Parametric Statistical Change Point Analysis
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Parametric Statistical Change Point Analysis

Authors: Jie Chen
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Type: BOOK - Published: 2013-11-11 - Publisher: Springer Science & Business Media

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Recently there has been a keen interest in the statistical analysis of change point detec tion and estimation. Mainly, it is because change point problems can b
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Limit Theorems in Change-Point Analysis

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Type: BOOK - Published: 1997-12-29 - Publisher: John Wiley & Sons

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Change-point problems arise in a variety of experimental and mathematical sciences, as well as in engineering and health sciences. This rigorously researched te
Climate Time Series Analysis
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Climate Time Series Analysis

Authors: Manfred Mudelsee
Categories: Science
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Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial depend