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A New Framework of Smoothed Location Model with Multiple Correspondence Analysis

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Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015)

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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.

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Acknowledgment

Author would like to thank to Universiti Utara Malaysia, Malaysia for financial support.

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Authors and Affiliations

  1. School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Sintok, Malaysia

    Hashibah binti Hamid

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  1. Hashibah binti Hamid
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Correspondence to Hashibah binti Hamid .

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Editors and Affiliations

  1. Universiti Teknologi MARA, Kedah, Merbok, Malaysia

    Abd-Razak Ahmad

  2. Universiti Teknologi MARA, Kedah, Merbok, Malaysia

    Liew Kee Kor

  3. Universiti Teknologi MARA, Kedah, Merbok, Malaysia

    Illiasaak Ahmad

  4. Universiti Teknologi Mara, Kedah, Merbok, Malaysia

    Zanariah Idrus

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Hamid, H.b. (2017). A New Framework of Smoothed Location Model with Multiple Correspondence Analysis. In: Ahmad, AR., Kor, L., Ahmad, I., Idrus, Z. (eds) Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015). Springer, Singapore. https://doi.org/10.1007/978-981-10-2772-7_12

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  • DOI: https://doi.org/10.1007/978-981-10-2772-7_12

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  • Online ISBN: 978-981-10-2772-7

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