Open AccessPEMILIHAN PARAMETER PENGHALUS DALAM REGRESI SPLINE LINIER
Author(s) -
Agustini Tripena Br. Sb.
Publication year - 2011
Publication title -
jurnal ilmiah matematika dan pendidikan matematika (jmp)/jurnal ilmiah matematika dan pendidikan matematika
Language(s) - English
Resource type - Journals
eISSN - 2550-0422
pISSN - 2085-1456
DOI - 10.20884/1.jmp.2011.3.1.2969
Subject(s) - smoothing , spline (mechanical) , mean squared error , mathematics , smoothing spline , statistics , selection (genetic algorithm) , cross validation , engineering , computer science , artificial intelligence , structural engineering , spline interpolation , bilinear interpolation
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.