Tekrarlanan Ölçümlerde Varyans-Kovaryans Unsurlarının Tahmin Edilmesinde Farklı Yaklaşımların Performanslarının Karşılaştırılması

Hayvan ıslahında tekrarlanan gözlem değerleri giderek önem kazanmakta olan bir konudur. Bu çalışmada tekrarlanan gözlem değerlerini içeren veri setlerinin analiz ve parametre tahminleri için kullanılan yöntem ve metodlar karşılaştırılmıştır. Bu modellere alternatif olarak Ali-Schaeffer eğri fonksiyonunun uyumuyla oluşturulan kovaryans fonksiyon yaklaşımlı şansa bağlı regresyon modelinin kullanımı araştırılmıştır. Bu amaçla süt sığırları için tutulmuş olan kayıtlardan sağlanan bir veri tabanı esas alınarak simulasyonla elde edilmiş bir veri seti üzerinde çalışılmıştır.Zamana bağlı değişimin geçerli olduğu denetim günü verimleri için uyumu yapılan modellerden uyum büyükten küçüğe sırasıyla KF+RRM (kovaryans fonksiyonu yaklaşımlı şansa bağlı regresyon modeli), DRRM (doğrudan şansa bağlı regresyon modeli), TM (tekrarlanabilen model), ORM (oto-regresif model) ve HM (hayvan model)’de olmuştur. Hatalar arası oto-korelasyon yapısı en iyi KF-RRM ve ORM modellerinde açıklanabilmiştir. Tahmin edilen parametreler, varynslar için karşılaştırılmış ve en hassas parametre tahminleri KF-RRM sonuçlarından elde edilmiş bunu DRRM izlemiştir.

Anahtar Kelimeler:

Şansa bağlı regresyon, DFREML, tekrarlanan ölçümler, ortogonal polinom, oto-korelasyon.

Comparison of the Performance of Different Approaches in repeated Measurements for Estimation of (Co)variance Components

In animal breeding, repeated measurements are important. In this study, we compared the methods and models which are used in the analysis of data sets which contain the repeated measurements and the estimation of parameters. Morover, as an alternative method, random regression procedure which used the approach of covariance functions and was formed by compatibility of Ali-Schaeffer curve function was investigated. A data set was generated by simulation from retrospective records of dairy cattle. Fitting of the tested models for test-day yields in time were ranked from the best to the worst were CF-RRM (covariance function random regression model), DRRM (direct RRM), RM (repeatability model), ARM (auto-regresive model) and AM (animal model) respectively. It was determinded that the best models which explain the auto-correlation structure among the experimental errors were CF-RRM and ARM. Predicted parameters were compared for variances and the most sensitive estimation of parameters were obtained by CF-RRM. It was followed by DRRM.

Keywords:

Random regression, DFREML, repeated measurements, orthogonal polinomial, auto-correlation.,

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