Publication
Title
Analyzing supersaturated designs with entropic measures
Author
Abstract
A supersaturated design is a design for which there are fewer runs than effects to be estimated. In this paper, we propose a method for screening out the important factors from a large set of potentially active variables, based on an information theoretical approach. Three entropy measures: Rényi entropy, Tsallis entropy and HavrdaCharvát entropy, have been associated with the measure of information gain, in order to identify the significant factors using data and assuming generalized linear models. The investigation of the proposed method performance and the comparison of each entropic measure application have been accomplished through simulation experiments. A noteworthy advantage of this paper is the use of generalized linear models for analyzing data from supersaturated designs, a fact that, to the best of our knowledge, has not yet been studied.
Language
English
Source (journal)
Journal of statistical planning and inference. - Amsterdam
Publication
Amsterdam : 2011
ISSN
0378-3758
Volume/pages
141:3(2011), p. 1307-1312
ISI
000285227100021
Full text (Publishers DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 25.11.2010
Last edited 10.04.2017
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