CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization

Date

2012-01-01

Author

Weber, Gerhard-Wilhelm
Batmaz, İnci
Köksal, Gülser
Taylan, Pakize
Yerlikaya-Ozkurt, Fatma

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Regression analysis is a widely used statistical method for modelling relationships between variables. Multivariate adaptive regression splines (MARS) especially is very useful for high-dimensional problems and fitting nonlinear multivariate functions. A special advantage of MARS lies in its ability to estimate contributions of some basis functions so that both additive and interactive effects of the predictors are allowed to determine the response variable. The MARS method consists of two parts: forward and backward algorithms. Through these algorithms, it seeks to achieve two objectives: a good fit to the data, but a simple model. In this article, we use a penalized residual sum of squares for MARS as a Tikhonov regularization problem, and treat this with continuous optimization technique, in particular, the framework of conic quadratic programming. We call this new approach to MARS as CMARS, and consider it as becoming an important complementary and model-based alternative to the backward stepwise algorithm. The performance of CMARS is also evaluated using different data sets with different features, and the results are discussed.

Subject Keywords

Conic quadratic programming, Tikhonov regularization, Multivariate adaptive regression splines, Nonparametric regression, Interior point methods

URI

https://hdl.handle.net/11511/46678

Journal

INVERSE PROBLEMS IN SCIENCE AND ENGINEERING

DOI

https://doi.org/10.1080/17415977.2011.624770

Collections

Department of Statistics, Article

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Citation Formats

G.-W. Weber, İ. Batmaz, G. Köksal, P. Taylan, and F. Yerlikaya-Ozkurt, “CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization,” INVERSE PROBLEMS IN SCIENCE AND ENGINEERING, pp. 371–400, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46678.