An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression

AŞIKGİL, BARIŞ

An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression

Barış AŞIKGİL (Mimar Sinan Güzel Sanatlar Üniversitesi)

Gazi University Journal of Science

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Yıl: 2018 Cilt: 31 Sayı: 4 Sayfa Aralığı: 1268 - 1282 Metin Dili: İngilizce İndeks Tarihi: 19-02-2020

An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression

Öz:

Ordinary least squares method is usually used for parameter estimation in multiple linearregression models when all regression assumptions are satisfied. One of the problems inmultiple linear regression analysis is the presence of serially correlated disturbances. Serialcorrelation can be formed by autoregressive or moving average models. There are manystudies in the literature including parameter estimation in regression models especially withautoregressive disturbances. The motivation of this study is that whether serially correlateddisturbances are defined by a different type of nonlinear process and how this process isanalyzed in multiple linear regression. For this purpose, a nonlinear time series processknown as self-exciting threshold autoregressive model is used to generate disturbances inmultiple linear regression models. Two-stage least squares method used in the presence ofautoregressive disturbances is adapted for dealing with this new situation and comprehensiveexperiments are performed in order to compare efficiencies of the proposed method with theothers. According to numerical results, the proposed method can outperform under the typeof self-exciting threshold autoregressive autocorrelation problem when compared to ordinaryleast squares and two-stage least squares.

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APA	AŞIKGİL B (2018). An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. , 1268 - 1282.
Chicago	AŞIKGİL BARIŞ An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. (2018): 1268 - 1282.
MLA	AŞIKGİL BARIŞ An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. , 2018, ss.1268 - 1282.
AMA	AŞIKGİL B An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. . 2018; 1268 - 1282.
Vancouver	AŞIKGİL B An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. . 2018; 1268 - 1282.
IEEE	AŞIKGİL B "An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression." , ss.1268 - 1282, 2018.
ISNAD	AŞIKGİL, BARIŞ. "An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression". (2018), 1268-1282.

APA	AŞIKGİL B (2018). An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. Gazi University Journal of Science, 31(4), 1268 - 1282.
Chicago	AŞIKGİL BARIŞ An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. Gazi University Journal of Science 31, no.4 (2018): 1268 - 1282.
MLA	AŞIKGİL BARIŞ An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. Gazi University Journal of Science, vol.31, no.4, 2018, ss.1268 - 1282.
AMA	AŞIKGİL B An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. Gazi University Journal of Science. 2018; 31(4): 1268 - 1282.
Vancouver	AŞIKGİL B An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression. Gazi University Journal of Science. 2018; 31(4): 1268 - 1282.
IEEE	AŞIKGİL B "An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression." Gazi University Journal of Science, 31, ss.1268 - 1282, 2018.
ISNAD	AŞIKGİL, BARIŞ. "An AdaptedApproach for Self-ExcitingThreshold Autoregressive Disturbances in Multiple Linear Regression". Gazi University Journal of Science 31/4 (2018), 1268-1282.