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Minmad yöntemi ile rasgele bloklar model denklemindeki parametrelerin kestirimi

Authors: Şanli, Kamile;

Minmad yöntemi ile rasgele bloklar model denklemindeki parametrelerin kestirimi

Abstract

The estimation of parameters is quite important in statistics. The statisticians has made large amounts of studies on this subject. Especially by the 1970's, the problem of estimation has become more often to be solved by the optimization methods. In this study, due to the importance of optimization methods in statistics, the parameters in the randomized block model equation is aimed to be estimate. On the last section which is the original part of this study, goal programming model is suggested for the estimation of the parameters in the randomized block model compared with the LSD model. 1999, 87 pagesKEY WORDS: Minmad (Minimizing mean absolute deviations), Goal programming, Randomized block design, Simplex algorithm.

İstatistikte parametre tahmini oldukça önemlidir. İstatistikçiler bu konuda bir çok çalışma yapmaktadırlar. Özellikle 1970'li yıllardan sonra bu tahmin probleminin optimizasyon yöntemleri ile çözümlenmesi artmıştır. Bu çalışmada da İstatistik' te Optimizasyon yöntemlerinin önemi olgusundan hareketle rasgele bloklar model denklemindeki parametrelerin tahmini amaçlanmıştır. Çalışmanın özgün yanını oluşturan son bölümde rasgele bloklar model denklemindeki parametrelerin tahmini için heder programlama modeli önerilmiştir ve elde edilen sonuçlar EKK yöntemi ile karşılaştırılıuıştır. 1999, 87 sayfa ANAHTAR KELİMELER : i/ linin ad (En küçük ortalama mutlak sapma), Hedef programlama, Rasgele blok, Simpleks algoritması

98

Keywords

Minnad method, İstatistik, Statistics, Parameter estimation, Goal programming, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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