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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Marques, A., Ferreira, A. S. & Cardoso, M. G. M. S. (2013). Selection of variables in Discrete Discriminant Analysis. Biometrical Letters. 50 (1)
Exportar Referência (IEEE)
A. Marques et al.,  "Selection of variables in Discrete Discriminant Analysis", in Biometrical Letters, vol. 50, no. 1, 2013
Exportar BibTeX
@article{marques2013_1732407694106,
	author = "Marques, A. and Ferreira, A. S. and Cardoso, M. G. M. S.",
	title = "Selection of variables in Discrete Discriminant Analysis",
	journal = "Biometrical Letters",
	year = "2013",
	volume = "50",
	number = "1",
	doi = "10.2478/bile-2013-0013",
	url = "https://www.degruyter.com/view/j/bile.2013.50.issue-1/bile-2013-0013/bile-2013-0013.xml"
}
Exportar RIS
TY  - JOUR
TI  - Selection of variables in Discrete Discriminant Analysis
T2  - Biometrical Letters
VL  - 50
IS  - 1
AU  - Marques, A.
AU  - Ferreira, A. S.
AU  - Cardoso, M. G. M. S.
PY  - 2013
SN  - 1896-3811
DO  - 10.2478/bile-2013-0013
UR  - https://www.degruyter.com/view/j/bile.2013.50.issue-1/bile-2013-0013/bile-2013-0013.xml
AB  - In Discrete Discriminant Analysis one often has to deal with dimensionality problems. In fact, even a moderate number of explanatory variables leads to an enormous number of possible states (outcomes) when compared to the number of objects under study, as occurs particularly in the social sciences, humanities and health-related elds. As a consequence, classi cation or discriminant models may exhibit poor performance due to the large number of parameters to be estimated. In the present paper, we discuss variable selection techniques which aim to address the issue of dimensionality. We speci cally perform classi cation using a combined model approach. In this setting, variable selection is particularly pertinent, enabling the handling of degrees of freedom and reducing computational cost. 
ER  -