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Sequential order statistics with an order statistics prior

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Title: Sequential order statistics with an order statistics prior
Authors: Burkschat, M.1, Kamps, U.2 udo.kamps@rwth-aachen.de, Kateri, M.3
Source: Journal of Multivariate Analysis. Sep2010, Vol. 101 Issue 8, p1826-1836. 11p.
Subjects: Sequential analysis, Statistics, Distribution (Probability theory), Parameter estimation, Multivariate analysis, Exponential functions
Abstract: Abstract: In the model of sequential order statistics, prior distributions are considered for the model parameters, which, for example, describe increasing load put on remaining components. Gamma priors are examined as well as priors out of a class of extended truncated Erlang distributions (ETED), which is introduced along with some properties. The choice of independent priors in both set-ups leads to respective independent, conjugate posterior distributions for the model parameters of sequential order statistics. Since, in practical applications, the model parameters will often be increasingly ordered, a multivariate prior is applied being the joint distribution of common ETED-order statistics. Whatever baseline distribution of the sequential order statistics is chosen, the joint posterior distribution turns out to be a Weinman multivariate exponential distribution. Posterior moments are given explicitly, and HPD credible sets for the model parameters are stated. [Copyright &y& Elsevier]
Copyright of Journal of Multivariate Analysis is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 50982120
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22Sequential+analysis%22">Sequential analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Exponential+functions%22">Exponential functions</searchLink>
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  Data: Abstract: In the model of sequential order statistics, prior distributions are considered for the model parameters, which, for example, describe increasing load put on remaining components. Gamma priors are examined as well as priors out of a class of extended truncated Erlang distributions (ETED), which is introduced along with some properties. The choice of independent priors in both set-ups leads to respective independent, conjugate posterior distributions for the model parameters of sequential order statistics. Since, in practical applications, the model parameters will often be increasingly ordered, a multivariate prior is applied being the joint distribution of common ETED-order statistics. Whatever baseline distribution of the sequential order statistics is chosen, the joint posterior distribution turns out to be a Weinman multivariate exponential distribution. Posterior moments are given explicitly, and HPD credible sets for the model parameters are stated. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Journal of Multivariate Analysis is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.jmva.2010.03.017
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 1826
    Subjects:
      – SubjectFull: Sequential analysis
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Distribution (Probability theory)
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      – SubjectFull: Parameter estimation
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      – SubjectFull: Multivariate analysis
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      – SubjectFull: Exponential functions
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      – TitleFull: Sequential order statistics with an order statistics prior
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              Text: Sep2010
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