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Multivariate isotonic regression and its algorithms
Hoffmann, Linda Hu, Xiaomi
Hoffmann, Linda
Hu, Xiaomi
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2009-05-01
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Conference paper
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Hoffmann, Linda and Xiaomi Hu(2009) . Multivariate Isotonic Regression and Its Algorithms. In Proceedings: 5th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p. 38-39
Abstract
We use regression functions, which are the means of random variables, to interpret statistical inference. Often an order is imposed on the values of the regression function. Thus, we refer to the regression as an order restricted regression or an isotonic regression. In this paper we explain how to calculate multivariate isotonic regression. However, we investigate the case
for a particular restriction on our elements. We impose relations between elements of the same row but not between rows. The technique is to decompose our multivariate model into univariate models so that prior knowledge about the simpler case can be used. Finally, we propose an algorithm to calculate multivariate isotonic regression. This algorithm could then be converted into a computer program.
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Description
Paper presented to the 5th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Hughes Metropolitan Complex, Wichita State University, May 1, 2009.
Research completed at the Department of Mathematics & Statistics, College of Liberal Arts & Sciences
Research completed at the Department of Mathematics & Statistics, College of Liberal Arts & Sciences
Publisher
Wichita State University. Graduate School
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Series
GRASP
v.5
v.5