A new difference-based weighted mixed Liu estimator in partially linear models

AKDENİZ E., Akdeniz F., Roozbeh M.

STATISTICS, cilt.52, sa.6, ss.1309-1327, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 52 Sayı: 6
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/02331888.2018.1511715
  • Dergi Adı: STATISTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1309-1327
  • Anahtar Kelimeler: Difference-based estimator, generalized Liu estimator, generalized difference-based weighted mixed Liu estimator, partially linear model, weighted mixed estimator, RIDGE ESTIMATORS, REGRESSION, IMPROVEMENT, PARAMETERS, VARIANCE
  • Marmara Üniversitesi Adresli: Evet

Özet

In this paper, a generalized difference-based estimator is introduced for the vector parameter beta in the partially linear model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter beta. Under the linear stochastic constraint r = R beta + e, a new generalized difference-based weighted mixed Liu estimator is introduced. The performance of this estimator over the generalized difference-based weighted mixed estimator and the generalized difference-based Liu estimator in terms of the mean squared error matrix criterion is investigated. Then, a method to select the biasing parameter d and non-stochastic weight. is considered. The efficiency properties of the newestimator are illustrated by a simulation study. Finally, the performance of the new estimator is evaluated for a real data set.