Abstract
Efectivity of Additive Spline for Partial Least Square Method in Regression Model Estimation. Additive Spline of Partial Least Square method (ASPL) as one generalization of Partial Least Square (PLS) method. ASPLS method can be acommodation to non linear and multicollinearity case of predictor variables. As a principle, The ASPLS method approach is cahracterized by two idea. The first is to used parametric transformations of predictors by spline function; the second is to make ASPLS components mutually uncorrelated, to preserve properties of the linear PLS components. The performance of ASPLS compared with other PLS method is illustrated with the fisher economic application especially the tuna fish production.
References
[1] J. Fox, G. Monette, J. Amer. Statist. Assoc. 87(1992) 417. [2] E.J. Wegman, I. W. Wright, J. Amer. Statist. Assoc. 78 (1983) 425. [3] I.K.G. Sukarsa, Tesis, Program Pascasarjana Institut Pertanian Bogor, Indonesia, 2000. [4] J.F. Durand, R. Sabatier, J. Amer. Statist. Assoc. 92 (1997) 1546. [5] T.W. Nurani, S.H. Wisudo, M.P. Sobari, Studi Perbandingan Kajian Tekno-ekonomi Usaha Perikanan Longline Untuk Fresh dan Tuna, Laporan Penelitian OPF IPB Jurusan Sumberdaya Perikanan, Institut Pertanian Bogor, Bogor, 1997
Recommended Citation
Bilfarsah, Ahmad
(2023)
"EFEKTIFITAS METODE ADITIF SPLINE KUADRAT TERKECIL PARSIAL DALAM PENDUGAAN MODEL REGRESI,"
Makara Journal of Science: Vol. 9:
Iss.
1, Article 12.
Available at:
https://scholarhub.ui.ac.id/science/vol9/iss1/12
