Exportar Publicação

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) 
Curto, J. D. & Pinto, J. C. (2007). New multicollinearity indicators in linear regression models. International Statistical Review. 75 (1), 114-121
Exportar Referência (IEEE) 
J. J. Curto and J. C. Pinto,  "New multicollinearity indicators in linear regression models", in Int. Statistical Review, vol. 75, no. 1, pp. 114-121, 2007
Exportar BibTeX 
@article{curto2007_1732199299133,
	author = "Curto, J. D. and Pinto, J. C.",
	title = "New multicollinearity indicators in linear regression models",
	journal = "International Statistical Review",
	year = "2007",
	volume = "75",
	number = "1",
	doi = "10.1111/j.1751-5823.2007.00007.x",
	pages = "114-121",
	url = "http://onlinelibrary.wiley.com/doi/10.1111/j.1751-5823.2007.00007.x/abstract"
}
Exportar RIS 
TY  - JOUR
TI  - New multicollinearity indicators in linear regression models
T2  - International Statistical Review
VL  - 75
IS  - 1
AU  - Curto, J. D.
AU  - Pinto, J. C.
PY  - 2007
SP  - 114-121
SN  - 0306-7734
DO  - 10.1111/j.1751-5823.2007.00007.x
UR  - http://onlinelibrary.wiley.com/doi/10.1111/j.1751-5823.2007.00007.x/abstract
AB  - Correlation is an important statistical issue for the Ordinary Least Squares estimates and for data-reduction techniques, such as the Factor and the Principal Components analyses. In this paper we propose new indicators for the multicollinearity problem in the multiple linear regression model.
ER  -