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Analyzing supersaturated designs with entropic measures

Analyzing supersaturated designs with entropic measures
Analyzing supersaturated designs with entropic measures
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 Havrda–Charvát 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.

0378-3758
1307-1312
Koukouvinos, C.
3c626a53-575f-4c62-9b9a-a949f717764b
Massou, E.
c6536a82-e77b-41b4-8c5a-968b8dec63f1
Mylona, K.
b44af287-2d9f-4df8-931c-32d8ab117864
Parpoula, C.
0ec69647-7fec-4ae1-8103-cefad31fe255
Koukouvinos, C.
3c626a53-575f-4c62-9b9a-a949f717764b
Massou, E.
c6536a82-e77b-41b4-8c5a-968b8dec63f1
Mylona, K.
b44af287-2d9f-4df8-931c-32d8ab117864
Parpoula, C.
0ec69647-7fec-4ae1-8103-cefad31fe255

Koukouvinos, C., Massou, E., Mylona, K. and Parpoula, C. (2011) Analyzing supersaturated designs with entropic measures. Journal of Statistical Planning and Inference, 141 (3), 1307-1312. (doi:10.1016/j.jspi.2010.10.001).

Record type: Article

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 Havrda–Charvát 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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e-pub ahead of print date: 17 October 2010
Published date: March 2011
Organisations: Statistics

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Local EPrints ID: 336776
URI: http://eprints.soton.ac.uk/id/eprint/336776
ISSN: 0378-3758
PURE UUID: 254a6037-bb7c-4bd0-abc5-a0f582d8b501

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Date deposited: 03 Apr 2012 16:06
Last modified: 14 Mar 2024 10:46

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Contributors

Author: C. Koukouvinos
Author: E. Massou
Author: K. Mylona
Author: C. Parpoula

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