Reproducing Kernel Hilbert space and penalized weighted least square in nonparametric regression

Suhartono

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Reproducing Kernel Hilbert Space (RKHS) play a central role to solve the Penalized Weighted Least Square (PWLS) in Spline Estimator of nonparametric regression analysis. The purposes of this research is to obtain the RKHS approach in PWLS to solve the estimator of regression curve. Base of RKHS, the curve nonparametric regression form is f (x) = Td + Vc. Solving the weighted of PLWS coming from variance-covariance Ŵ is equals to solving the Σ11.111.2,..Σ22.r,...Σ12.11,...Σ12.rr.For

Original languageEnglish
Pages (from-to)7289-7300
Number of pages12
JournalApplied Mathematical Sciences
Volume8
Issue number145-148
DOIs
Publication statusPublished - 2014

Keywords

  • Hilbert space
  • PWLS
  • Reproducing Kernel

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