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

Year 2018, Volume: 5 Issue: 3, 310 - 316, 26.07.2018

Serhat Arslan , Mehmet Kazım Kara

https://doi.org/10.30910/turkjans.448372

Abstract

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.

Keywords

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

Abstract

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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