TY  - GEN
Y1  - 1995/10//
KW  - Convex contrast; bivariate sample; backward-induction algorithm; convex function; nonparametric analysis; real-valued response; treatment effect; special choice; recursive relation
A1  - Müller, D.W.
N2  - 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.
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/20899/
CY  - Heidelberg
TI  - A Backward-Induction Algorithm for Computing the best ConvexContrast of two Bivariate Samples
ID  - heidok20899
AV  - public
N1  - Erschienen in: Journal of Computational and Graphical Statistics, Sept. 1999
EP  - 14
ER  -