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An Application of Functional Multivariate Regression Model to Multiclass Classification

Author

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  • Krzyśko Mirosław

    (Inter-Faculty Department of Mathematics and Statistics, The President Stanisław Wojciechowski State University of Applied Sciences in Kalisz, Kalisz, ; Poland .)

  • Smaga Łukasz

    (Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Kalisz, ; Poland)

Abstract

In this paper, the scale response functional multivariate regression model is considered. By using the basis functions representation of functional predictors and regression coefficients, this model is rewritten as a multivariate regression model. This representation of the functional multivariate regression model is used for multiclass classification for multivariate functional data. Computational experiments performed on real labelled data sets demonstrate the effectiveness of the proposed method for classification for functional data.

Suggested Citation

  • Krzyśko Mirosław & Smaga Łukasz, 2017. "An Application of Functional Multivariate Regression Model to Multiclass Classification," Statistics in Transition New Series, Statistics Poland, vol. 18(3), pages 433-442, September.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:3:p:433-442:n:10
    DOI: 10.21307/stattrans-2016-079
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    References listed on IDEAS

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    1. Jacques, Julien & Preda, Cristian, 2014. "Model-based clustering for multivariate functional data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 92-106.
    2. Berrendero, J.R. & Justel, A. & Svarc, M., 2011. "Principal components for multivariate functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2619-2634, September.
    3. Matsui, Hidetoshi, 2014. "Variable and boundary selection for functional data via multiclass logistic regression modeling," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 176-185.
    4. Collazos, Julian A.A. & Dias, Ronaldo & Zambom, Adriano Z., 2016. "Consistent variable selection for functional regression models," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 63-71.
    5. Matsui, Hidetoshi & Konishi, Sadanori, 2011. "Variable selection for functional regression models via the L1 regularization," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3304-3310, December.
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