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Export Reference (APA) 
Brochado, A. & Martins, F. V. (2014). Identifying small market segments with mixture regression models. International Journal of Latest Trends in Finance and Economics Sciences. 4 (4), 812-820
Export Reference (IEEE) 
A. M. Brochado and F. V. Martins,  "Identifying small market segments with mixture regression models", in Int. Journal of Latest Trends in Finance and Economics Sciences, vol. 4, no. 4, pp. 812-820, 2014
Export BibTeX 
@article{brochado2014_1765919927663,
	author = "Brochado, A. and Martins, F. V.",
	title = "Identifying small market segments with mixture regression models",
	journal = "International Journal of Latest Trends in Finance and Economics Sciences",
	year = "2014",
	volume = "4",
	number = "4",
	pages = "812-820",
	url = "http://ojs.excelingtech.co.uk/index.php/IJLTFES/article/view/812/615"
}
Export RIS 
TY  - JOUR
TI  - Identifying small market segments with mixture regression models
T2  - International Journal of Latest Trends in Finance and Economics Sciences
VL  - 4
IS  - 4
AU  - Brochado, A.
AU  - Martins, F. V.
PY  - 2014
SP  - 812-820
SN  - 2047-0916
UR  - http://ojs.excelingtech.co.uk/index.php/IJLTFES/article/view/812/615
AB  - The purpose of this work is to determine howwell criteria designed to help the selection of theadequate number of market segments perform inrecovering small niche market segments, in mixtureregressions of normal data. As in real world data thetrue number of market segments is unknown, theresults of this study are based on experimental data.The simulation experiment compares 27 segmentretention criteria, comprising 14 information criteriaand 13 classification-based criteria. The results revealthat AIC3, AIC4, HQ, BIC, CAIC, ICLBIC andICOMPLBIC are the best criteria in recovering smallniche segments and encourage its use.
ER  -