Ağaçların Çap-Boy Modellemesine İlişkin Otokorelasyon Probleminin Giderilmesinde Karışık Etkili Doğrusal Olmayan Regresyon Modelleri ile Otoregresif Regresyon Modellerinin Etkinliğinin Karşılaştırılması

Year 2019, Volume: 5 Issue: 1, 17 - 27, 07.08.2019

İlker Ercanlı Doğa Eyüboğlu

Abstract

Ağaçların
çap-boy ilişkilerinin modellenmesinde, Doğrusal Olmayan Regresyon modeli yanında Karışık Etkili Doğrusal Olmayan
Regresyon modeli ile AR(1), AR(2), MA(1), MA(2), ARMA (1,1) ve ARMA (2,2) gibi
çeşitli Otoregresif modellerin tahmin başarılıları ve farklı yapıdaki
meşcerelerden elde edilen hiyerarşik verilerin kullanımıyla oluşan
Otokorelasyon sorununa çözüm sunma kapasiteleri karşılaştırılmıştır.  Doğrusal Olmayan Regresyon Analizine ait
başarı ölçütlerine göre   (RMSE=1.761,
RMSE% =12.450, R²=0.838, AIC=316.167 ve BIC=912.207), gerek
Otoregresif modelleme gerekse Karışık Etkili Doğrusal Olmayan Regresyon
Modellemesinin kullanım ile önemli oranda iyileşmeler elde edilmiştir. En
başarılı olarak belirlenen a parametresi rasgele olan Karışık Etkili Regresyon
Modelinde, RMSE değeri; 1.174, RMSE% değeri; 8.300, R²değeri;0.928, AIC değeri; 93.959 ve BIC değeri ise; 689.999 olarak hesaplanmış
ve bu bakımdan da RMSE değerinde % 33.33, RMSE% değerinde % 33.33, R²
değerinde % 10.74, AIC değerinde % 70.28 ce BIC değerinde % 24.36 iyileşme elde
edilmiştir. Tahmin başarı
ölçütlerindeki iyileşmeler yanında Karışık Etkili Regresyon Modeli ile çeşitli Otoregresif
modellere ilişkin hesaplanan Durbin-Watson katsayısı 2’ye yakın olarak elde
edilmiş ve test sonucu olarak da herhangi bir Otokorelasyon saptanmamıştır.

Keywords

Çap-Boy Tahmini, Otokorelasyon, Karışık Etkili Regresyon Modeli

References

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