Accelerating the Pool-Adjacent-Violators Algorithm for Isotonic Distributional Regression

In the context of estimating stochastically ordered distribution functions, the pool-adjacent-violators algorithm (PAVA) can be modified such that the computation times are reduced substantially. This is achieved by studying the dependence of antitonic weighted least squares fits on the response vec...

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Bibliographic Details
Published inMethodology and computing in applied probability Vol. 24; no. 4; pp. 2633 - 2645
Main Authors Henzi, Alexander, Mösching, Alexandre, Dümbgen, Lutz
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2022
Springer Nature B.V
Subjects
Algorithms
Approximation
Business and Management
Distribution functions
Economics
Electrical Engineering
Life Sciences
Mathematics and Statistics
Random variables
Statistics
Monotone regression
62G30
62-08
62G08
Sequential computation
Weighted least squares
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Summary:In the context of estimating stochastically ordered distribution functions, the pool-adjacent-violators algorithm (PAVA) can be modified such that the computation times are reduced substantially. This is achieved by studying the dependence of antitonic weighted least squares fits on the response vector to be approximated.
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ISSN:1387-5841
1573-7713
DOI:10.1007/s11009-022-09937-2