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

Alexander Henzi (), Alexandre Mösching () and Lutz Dümbgen ()
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Alexander Henzi: University of Bern
Alexandre Mösching: Georg-August-University of Göttingen
Lutz Dümbgen: University of Bern

Methodology and Computing in Applied Probability, 2022, vol. 24, issue 4, 2633-2645

Abstract: Abstract 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.

Keywords: Monotone regression; Sequential computation; Weighted least squares; 62G08; 62G30; 62-08 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11009-022-09937-2

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