Title
Analyzing supersaturated designs with entropic measures Analyzing supersaturated designs with entropic measures
Author
Faculty/Department
Faculty of Applied Economics
Publication type
article
Publication
Amsterdam ,
Subject
Economics
Mathematics
Source (journal)
Journal of statistical planning and inference. - Amsterdam
Volume/pages
141(2011) :3 , p. 1307-1312
ISSN
0378-3758
ISI
000285227100021
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
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.
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