Restricted ridge estimator in generalized linear models: Monte Carlo simulation studies on Poisson and binomial distributed responses


KURTOĞLU F. , Ozkale M. R.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.48, ss.1191-1218, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 48 Konu: 4
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1080/03610918.2017.1408822
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Sayfa Sayıları: ss.1191-1218

Özet

It is known that collinearity among the explanatory variables in generalized linear models (GLMs) inflates the variance of maximum likelihood estimators. To overcome multicollinearity in GLMs, ordinary ridge estimator and restricted estimator were proposed. In this study, a restricted ridge estimator is introduced by unifying the ordinary ridge estimator and the restricted estimator in GLMs and its mean squared error (MSE) properties are discussed. The MSE comparisons are done in the context of first-order approximated estimators. The results are illustrated by a numerical example and two simulation studies are conducted with Poisson and binomial responses.