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AN INTEGRATED APPROACH TO REGRESSION ANALYSIS IN MULTIPLE CORRESPONDENCE ANALYSIS AND COPULA BASED MODELS |
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PP: 67-87 |
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Author(s) |
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Jules J. S. de Tibeiro,
Pranesh Kumar,
Khine Khine S. Myat,
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Abstract |
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| In this paper, taking into account the possible development of serious disorders of
the proliferation of the plasmatic cells, we focus on a dataset concerning the prediction
among a chronic disease which has the higher risk of malignant transformation. The
purpose of this paper is to argue in favour of the use of multiple correspondence analysis
(MCA) as a powerful exploratory tool for such data. Following usual regression terminology,
we refer to the primary variable as the response variable and the others as explanatory or
predictive variables. As an alternative, a copula based methodology for prediction modeling
and an algorithm to stimulate data are proposed. |
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