In this paper, we describe some evolutionaryapproaches based on genetic algorithms to face the statisticalmodel selection problem using completely data-drivenalgorithms. As first, we propose an approach to selectmultivariate linear regression models as well as to buildARMA time series models. As second, we introduce amethodology to tackle the clustering problem in a modelbasedframework. We report the results from severalapplications and from simulated datasets and we compare theevolutionary approaches with some classical ones.

Evolutionary Approaches for Statistical Modelling / Minerva, Tommaso; Paterlini, Sandra. - STAMPA. - 2:(2002), pp. 2023-2028. (Intervento presentato al convegno WCCI 2002,Proc. of the Fourth Congress on Evolutionary Computation tenutosi a Honolulu, Haway nel May 2002) [10.1109/CEC.2002.1004554].

Evolutionary Approaches for Statistical Modelling

MINERVA, Tommaso;PATERLINI, Sandra
2002

Abstract

In this paper, we describe some evolutionaryapproaches based on genetic algorithms to face the statisticalmodel selection problem using completely data-drivenalgorithms. As first, we propose an approach to selectmultivariate linear regression models as well as to buildARMA time series models. As second, we introduce amethodology to tackle the clustering problem in a modelbasedframework. We report the results from severalapplications and from simulated datasets and we compare theevolutionary approaches with some classical ones.
2002
WCCI 2002,Proc. of the Fourth Congress on Evolutionary Computation
Honolulu, Haway
May 2002
2
2023
2028
Minerva, Tommaso; Paterlini, Sandra
Evolutionary Approaches for Statistical Modelling / Minerva, Tommaso; Paterlini, Sandra. - STAMPA. - 2:(2002), pp. 2023-2028. (Intervento presentato al convegno WCCI 2002,Proc. of the Fourth Congress on Evolutionary Computation tenutosi a Honolulu, Haway nel May 2002) [10.1109/CEC.2002.1004554].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/587768
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