Hamid, Hashibah (2016) A new framework of smoothed location model with multiple correspondence analysis. In: International Conference on Computing, Mathematics and Statistics (iCMS 2015), November 2015, Langkawi.

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Abstract

The implication of a considering large binary variables into the smoothed location model will create too many multinomial cells or lead to high multinomial cells and more worrying is that it will cause most of them are empty. We refer this situation as large sparsity problem. When large sparsity of multinomial cells occurs, the smoothed estimators of location model will be greatly biased, hence creating frustrating performance. At worst, the classification rules cannot be constructed. This issue has attracted this paper to further investigate and propose a new approach of the smoothed location model when facing with large sparsity problem.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015): Bridging Research Endeavors Editors: Ahmad, A.-R., Kor, L.K., Ahmad, I., Idrus, Z. (Eds.)ISBN 978-981-10-2772-7
Uncontrolled Keywords:	Location model; Classification rule; Empty cells; Multiple correspondence analysis; Large binary variables
Subjects:	Q Science > QA Mathematics
Divisions:	School of Quantitative Sciences
Depositing User:	PM.Dr. Hashibah Hamid
Date Deposited:	16 Apr 2017 08:58
Last Modified:	16 Apr 2017 08:58
URI:	https://repo.uum.edu.my/id/eprint/21576

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