Doğrusal Olmayan Regresyondaki Kendinden Eşik Değerli Otoregresif Hatalar Sorununa Uyarlamalı Bir Yaklaşım

Öz

Bu çalışma, doğrusal olmayan regresyon modellerinde kendinden eşik değerli otoregresif (KEDAR) hataların varlığında etkin parametre kestirimleri elde edebilmeyi amaçlamaktadır. Bu doğrultuda, otoregresif (AR) süreçlere karşı önerilen iki aşamalı en küçük kareler (İAEKK) yöntemi KEDAR süreçleri için ele alınacak ve etkin parametre kestirimleri elde edilebilmesi için uyarlamalı bir yaklaşım araştırılacaktır. Karesel çokterimli (polinomiyel) daraltma fonksiyonu kullanılarak İAEKK yöntemine bir uyarlama yapılıp bu yeni yaklaşımın etkinliği farklı senaryolar altında bir benzetim çalışması ile incelenecektir.

Anahtar Kelimeler

• Doğrusal Olmayan Regresyon
• Otokorelasyon
• Kendinden Eşik Değerli Otoregresif Süreçler
• Uyarlamalı İki Aşamalı Yaklaşım

An Adaptive Estimation Method for Nonlinear Regression with Self-Exciting Threshold Autoregressive Errors

Öz

This study aims to obtain efficient parameter estimates in the presence of self-exciting threshold autoregressive (SETAR) errors in nonlinear regression models. In this way, the two-stage least squares (TSLS) method proposed for autoregressive (AR) processes is discussed for SETAR processes and an adaptive approach is investigated to obtain efficient parameter estimates. An adaptation of TSLS method is made by using a quadratic polynomial tapering function and the efficiency of this new approach is examined with a simulation study under different scenarios.

Anahtar Kelimeler

• Nonlinear Regression
• Autocorrelation
• Self-Exciting Threshold Autoregressive Processes
• Adaptive Two-Stage Approach

Kaynakça

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