Loading...
Multivariate isotonic regression and its algorithms
Hoffmann, Linda
Hoffmann, Linda
Citations
Altmetric:
Files
Loading...
Thesis
Adobe PDF, 200.11 KB
Authors
Other Names
Location
Time Period
Advisors
Original Date
Digitization Date
Issue Date
2009-05
Type
Thesis
Genre
Keywords
Subjects (LCSH)
Electronic dissertations
Citation
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.
Table of Contents
Description
Thesis (M.S.)--Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics and Statistics
Publisher
Wichita State University