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http://dx.doi.org/10.7465/jkdi.2014.25.1.19

A polychotomous regression model with tensor product splines and direct sums  

Sim, Songyong (Department of Finance & Information Statistics, Hallym University)
Kang, Heemo (Department of Finance & Information Statistics, Hallym University)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.1, 2014 , pp. 19-26 More about this Journal
Abstract
In this paper, we propose a polychotomous regression model when independent variables include both categorical and numerical variables. For categorical independent variables, we use direct sums, and tensor product splines are used for continuous independent variables. We use BIC for varible selections criterior. We implemented the algorithm and apply the algorithm to real data. The use of direct sums and tensor products outperformed the usual multinomial logistic regression model.
Keywords
BIC; classification rate; test data; training data;
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Times Cited By KSCI : 7  (Citation Analysis)
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