Ridge-type pretest and shrinkage estimations in partially linear models

YÜZBAŞI B., Ahmed S. E., AYDIN D.

STATISTICAL PAPERS, vol.61, no.2, pp.869-898, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 61 Issue: 2
  • Publication Date: 2020
  • Doi Number: 10.1007/s00362-017-0967-8
  • Journal Name: STATISTICAL PAPERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, International Bibliography of Social Sciences, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, EconLit, zbMATH
  • Page Numbers: pp.869-898
  • Keywords: Pretest estimation, Shrinkage estimation, Ridge regression, Smoothing spline, Partially linear model, SMOOTHNESS PRIORS, ABSOLUTE PENALTY, REGRESSION, SELECTION
  • Inonu University Affiliated: Yes

Abstract

In this paper, we suggest pretest and shrinkage ridge regression estimators for a partially linear regression model, and compare their performance with some penalty estimators. We investigate the asymptotic properties of proposed estimators. We also consider a Monte Carlo simulation comparison, and a real data example is presented to illustrate the usefulness of the suggested methods.