Abstract

Semiparametric regression contains two components, i.e. parametric and nonparametric component. Semiparametric regression model is represented by {equation presented} and yti is response variable. It is assumed to have a linear relationship with the predictor variables {equation presented}. Random error εti, i = 1, ..., n, t = 1, ..., T is normally distributed with zero mean and variance σ2 and g(zti) is a nonparametric component. The results of this study showed that the PLS approach on longitudinal semiparametric regression models obtain estimators {equation presented}and {equation presented}. The result also show that bootstrap was valid on longitudinal semiparametric regression model with {equation presented} as nonparametric component estimator.

Original languageEnglish
Title of host publicationProceedings of the 7th SEAMS UGM International Conference on Mathematics and Its Applications 2015
Subtitle of host publicationEnhancing the Role of Mathematics in Interdisciplinary Research
EditorsYeni Susanti, Indah Emilia Wijayanti, Fajar Adi Kusumo, Irwan Endrayanto Aluicius
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735413542
DOIs
Publication statusPublished - 11 Feb 2016
Event7th SEAMS UGM International Conference on Mathematics and Its Applications: Enhancing the Role of Mathematics in Interdisciplinary Research - Yogyakarta, Indonesia
Duration: 18 Aug 201521 Aug 2015

Publication series

NameAIP Conference Proceedings
Volume1707
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference7th SEAMS UGM International Conference on Mathematics and Its Applications: Enhancing the Role of Mathematics in Interdisciplinary Research
Country/TerritoryIndonesia
CityYogyakarta
Period18/08/1521/08/15

Keywords

  • bootstrap
  • longitudinal semiparametric regression
  • nonparametric component
  • semiparametric regression

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