PEMILIHAN PARAMETER PENGHALUS DALAM REGRESI SPLINE LINIER - Agustini Tripena Br. Sb. (Jurusan Matematika FMIPA Universitas Jenderal Soedirman, 2011)
This paper discusses aselection of smoothing parameters for the linier spline regression estimation on the data of electrical voltage differences in the wastewater. The selection methods are based on the mean square errorr (MSE) and generalized cross validation (GCV). The results show that in selection of smooting paranceus the mean square error (MSE) method gives smaller value , than that of the generalized cross validatio (GCV) method. It means that for our data case the errorr mean square (MSE) is the best selection method of smoothing parameter for the linear spline regression estimation.