论文信息 - Relationship between Sums of Squares in Linear Regression and Semi-parametric Regression

Relationship between Sums of Squares in Linear Regression and Semi-parametric Regression

In this paper, the sum of squares in linear regression is reduced to sum of squares in semi-parametric regression. We indicated that different sums of squares in the linear regression are similar to various deviance statements in semi-parametric regression. In addition to, coefficient of the determination derived in linear regression model is easily generalized to coefficient of the determination of the semi-parametric regression model. Then, it is made an application in order to support the theory of the linear regression and semi-parametric regression. In this way, study is supported with a simulated data example. Keywords—Semi-parametric regression, Penalized Least Squares, Residuals, Deviance, Smoothing Spline.

Bilgin Senel | Dursun Aydın | Bilgin Şenel | D. Aydın

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