Ortalama Karesel Hata Matrisi Kriterine göre Yanlı Tahmin Ediciler Üzerine Çalışma

Çoklu doğrusallığa sahip regresyon modelleri, r- (k, d) sınıfı tahmincileri, ana bileşen regresyonu, Liu tipi tahminciler gibi çeşitli tahmincileri kullanarak ele alınabilir. Bu çalışmada, r- (k, d) sınıfı kestiricisinin, ana bileşenlerin regresyonu, Liu tipi tahmincileri ve sıradan en küçük kareler üzerinde, ortalama karesel hata matrisi (MSEM) kriteri açısından üstün olduğu koşulları belirledik. Son olarak, sayısal bir örnek ve Monte Carlo simülasyonu ile teorik sonuçları gösterdik.

Anahtar Kelimeler:

Liu-tipi tahmin edici, r-(k, d )Sınıf Tahmin Edici Temel bileşenler regresyonu, ortalama karesel hata matrisi

The Research on Biased Estimators Based on Mean Square Error Matrix Criteria

Regression models with multicollinearity can be tackled by using various estimators such as class estimators, principal components regression, Liu-type estimators. In this study, we defined conditions where the class estimator is superior over the biased estimators in terms of mean square error matrix (MSEM) criterion. Finally, we showed theoretical results by means of a numerical example and a simulation study.

Keywords:

r-(k, d) class estimator, Liu-type estimators (r-d) class estimator, Ordinary Ridge Regression Principal Component Regression, Mean square error matrix, Multicollinearity,

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