r-(k,d) sınıf tahmin edicisinin, ortalama karesel hata kriterine göre bazı yanlı tahmin ediciler ile karşılaştırılması

Year 2018, Volume: 11 Issue: 1, 13 - 22, 29.06.2018

Nilgün Yıldız

Abstract

En
küçük kareler, temel bileşenler ve Liu-tipi tahmin ediciler, çok değişkenli
regresyon modelleri için r-(k,d) sınıf tahmin edicilerin özel durumlarıdır.Bu
makalede r-(k,d) sınıf tahmin edicisini, en küçük kareler, temel bileşenler ve
Liu-tipi tahmin ediciler ile Matris Hata kareler ortalaması kriterine göre
karşılaştırılmıştır. Son olarak teorik sonuçları göstermek için sayısal bir
örnek ve bir Monte Carlo simülasyonu verilmektedir.Comparison of the   class estimators to some estimators by the mean square error matrix criteria

Keywords

Liu-tipi tahmin edici, r-(k, d )Sınıf Tahmin Edici, Temel bileşenler regresyonu, Matris Hata Kareler Ortalaması, Çoklu İç İlişki

Comparison of the class estimators to some estimators by the mean square error matrix criteria

Abstract

 The ordinary leastsquares, the
principal components regression and the Liu-type estimators are special cases
of ther-(k,d)class estimators, for regression
models with multicollinearity. In thisa rticle we derived conditions for the superiority
of ther-(k,d)
classestimatoroverotherestimatorssuch as ordinaryleastsquares,
principalcomponentandLiu-typeestimatorbased on the mean square error matrix(MSEM)criterion. Finally, a numericale xample
and a Monte Carlo simulation are also given to show the theoretical results.

Keywords

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

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