Robust parameter estimation of regression model with AR(p) error terms

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Tuac Y., GÜNEY Y., ŞENOĞLU B., ARSLAN O.

Communications in Statistics: Simulation and Computation, cilt.47, sa.8, ss.2343-2359, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 47 Sayı: 8
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/03610918.2017.1343839
  • Dergi Adı: Communications in Statistics: Simulation and Computation
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2343-2359
  • Anahtar Kelimeler: Autoregressive stationary process, Conditional maximum likelihood, Linear regression, Non-normal distributions, Robust estimation, T-DISTRIBUTION, LIKELIHOOD, AUTOREGRESSIONS
  • Ankara Üniversitesi Adresli: Evet

Özet

© 2018, © 2018 Taylor & Francis Group, LLC.In this article, we consider a linear regression model with AR(p) error terms with the assumption that the error terms have a t distribution as a heavy-tailed alternative to the normal distribution. We obtain the estimators for the model parameters by using the conditional maximum likelihood (CML) method. We conduct an iteratively reweighting algorithm (IRA) to find the estimates for the parameters of interest. We provide a simulation study and three real data examples to illustrate the performance of the proposed robust estimators based on t distribution.