Ordinary least squares method is usually used for parameter estimation in multiple linear regression models when all regression assumptions are satisfied. One of the problems in multiple linear regression analysis is the presence of serially correlated disturbances. Serial correlation can be formed by autoregressive or moving average models. There are many studies in the literature including parameter estimation in regression models especially with autoregressive disturbances. The motivation of this study is that whether serially correlated disturbances are defined by a different type of nonlinear process and how this process is analyzed in multiple linear regression. For this purpose, a nonlinear time series process known as selfexciting threshold autoregressive model is used to generate disturbances in multiple linear regression models. Twostage least squares method used in the presence of autoregressive disturbances is adapted for dealing with this new situation and comprehensive experiments are performed in order to compare efficiencies of the proposed method with the others. According to numerical results, the proposed method can outperform under the type of selfexciting threshold autoregressive autocorrelation problem when compared to ordinary least squares and twostage least squares.
Birincil Dil  en 

Konular  Mühendislik 
Dergi Bölümü  Statistics 
Yazarlar 

Bibtex  @araştırma makalesi { gujs384130,
journal = {GAZI UNIVERSITY JOURNAL OF SCIENCE},
issn = {},
eissn = {21471762},
address = {Gazi Üniversitesi},
year = {2018},
volume = {31},
pages = {1268  1282},
doi = {},
title = {An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression},
key = {cite},
author = {ASIKGIL, Barış}
} 
APA  ASIKGIL, B . (2018). An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression. GAZI UNIVERSITY JOURNAL OF SCIENCE, 31 (4), 12681282. Retrieved from http://dergipark.gov.tr/gujs/issue/40684/384130 
MLA  ASIKGIL, B . "An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression". GAZI UNIVERSITY JOURNAL OF SCIENCE 31 (2018): 12681282 <http://dergipark.gov.tr/gujs/issue/40684/384130> 
Chicago  ASIKGIL, B . "An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression". GAZI UNIVERSITY JOURNAL OF SCIENCE 31 (2018): 12681282 
RIS  TY  JOUR T1  An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression AU  Barış ASIKGIL Y1  2018 PY  2018 N1  DO  T2  GAZI UNIVERSITY JOURNAL OF SCIENCE JF  Journal JO  JOR SP  1268 EP  1282 VL  31 IS  4 SN  21471762 M3  UR  Y2  2018 ER  
EndNote  %0 Gazi University Journal of Science An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression %A Barış ASIKGIL %T An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression %D 2018 %J GAZI UNIVERSITY JOURNAL OF SCIENCE %P 21471762 %V 31 %N 4 %R %U 
ISNAD  ASIKGIL, Barış . "An Adapted Approach for SelfExciting Threshold Autoregressive Disturbances in Multiple Linear Regression". GAZI UNIVERSITY JOURNAL OF SCIENCE 31 / 4 (Aralık 2018): 12681282. 