eprintid: 20899
rev_number: 14
eprint_status: archive
userid: 2326
dir: disk0/00/02/08/99
datestamp: 2016-06-09 08:14:32
lastmod: 2016-06-24 08:44:13
status_changed: 2016-06-09 08:14:32
type: workingPaper
metadata_visibility: show
creators_name: Müller, D.W.
title: A Backward-Induction Algorithm for Computing the best ConvexContrast of two Bivariate Samples
subjects: 510
divisions: 110400
keywords: Convex contrast; bivariate sample; backward-induction algorithm; convex function; nonparametric analysis; real-valued response; treatment effect; special choice; recursive relation
note: Erschienen in: Journal of Computational and Graphical Statistics, Sept. 1999
abstract: For real-valued x(1), x(2), ... , x(n) with real-valued "responses"y(1), y(2), ... , y(n) and "scores" s(1), s(2), ... ,s(n) we solve the problem ofcomputing the maximum of C(k) = s(1) I {y(1) 3 k(x(1))}+ ... + s(n) I { ... } over allconvex functions k on the line. The article describes a recursive relation and analgorithm based on it to compute this value and an optimal k in O(n(3)) steps. Fora special choice of scores, max C(k) can be interpreted as a generalized (one-sided)Kolmogorov-Smirnov statistic to test for treatment effect in nonparametric analysisof covariance.
date: 1995-10
id_scheme: DOI
id_number: 10.11588/heidok.00020899
schriftenreihe_cluster_id: sr-10a
schriftenreihe_order: 29
ppn_swb: 1657257061
own_urn: urn:nbn:de:bsz:16-heidok-208995
language: eng
bibsort: MULLERDWABACKWARDI199510
full_text_status: public
place_of_pub: Heidelberg
pages: 14
citation:   Müller, D.W.  (1995) A Backward-Induction Algorithm for Computing the best ConvexContrast of two Bivariate Samples.  [Working paper]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/20899/1/beitrag.29.pdf