APLIKASI SPLINE ESTIMATOR TERBOBOT

Authors

  • I Nyoman Budiantara Fakultas Matematika dan Ilmu Pengetahuan Alam, Jurusan Statistika, Institut Teknologi 10 November Surabaya

:

https://doi.org/10.9744/jti.3.2.57-62

Keywords:

Weighted Spline, Nonparametric Regression, Penalized Least Square.

Abstract

We considered the nonparametric regression model : Zj = X(tj) + ej, j = 1,2,,n, where X(tj) is the regression curve. The random error ej are independently distributed normal with a zero mean and a variance s2/bj, bj > 0. The estimation of X obtained by minimizing a Weighted Least Square. The solution of this optimation is a Weighted Spline Polynomial. Further, we give an application of weigted spline estimator in nonparametric regression. Abstract in Bahasa Indonesia : Diberikan model regresi nonparametrik : Zj = X(tj) + ej, j = 1,2,,n, dengan X (tj) kurva regresi dan ej sesatan random yang diasumsikan berdistribusi normal dengan mean nol dan variansi s2/bj, bj > 0. Estimasi kurva regresi X yang meminimumkan suatu Penalized Least Square Terbobot, merupakan estimator Polinomial Spline Natural Terbobot. Selanjutnya diberikan suatu aplikasi estimator spline terbobot dalam regresi nonparametrik. Kata kunci: Spline terbobot, Regresi nonparametrik, Penalized Least Square.

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Published

2004-07-02

How to Cite

[1]
I. N. Budiantara, “APLIKASI SPLINE ESTIMATOR TERBOBOT”, Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 3, no. 2, pp. 57-62, Jul. 2004.