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English to Turkish Please (Yazar çok mu zor yazmış bana mı öyle geliyor)
1.       Hallederiz
136 posts
 31 Oct 2016 Mon 09:07 pm

If the law of distribution of mistakes is random (but is known), optimum on efficiency (at big n) estimations among all unbiased can be found on a methodMP. These estimations (A FORMULA) will not be linear on Y, despite of linearity(3). If to be limited by a class of linear estimations A FORMULAirrespective on the law of distribution of mistakes of an estimation with optimum properties turns out at the set kind of a matrix.


 


Let´s search for such estimation X of a vector of parameters that at its substitution in (3) sum of squares of deviation experimental Y from predictable Y=X.O was minimal. Thus we assume that: ...

2.       gokuyum
5049 posts
 20 Nov 2016 Sun 03:47 am

 

Quoting Hallederiz

If the law of distribution of mistakes is random (but is known), optimum on efficiency (at big n) estimations among all unbiased can be found on a methodMP. These estimations (A FORMULA) will not be linear on Y, despite of linearity(3). If to be limited by a class of linear estimations A FORMULAirrespective on the law of distribution of mistakes of an estimation with optimum properties turns out at the set kind of a matrix.

 

Let´s search for such estimation X of a vector of parameters that at its substitution in (3) sum of squares of deviation experimental Y from predictable Y=X.O was minimal. Thus we assume that: ...

My try: Hataların dağılımı kanunu rastgele ise (ama biliniyorsa), optimum etkinlikte (büyük n´de), tüm tarafsız tahminler metod MP´de bulunabilir. Bu tahminler (A formülü ) doğrusallığa rağmen( 3 ) Y´ de doğrusal olmayacaktır. Eğer A formülü bir sınıf doğrusal tahminlerle sınırlandırılacaksa hataların dağılımı kanunundan bağımsız olarak optimum özellikleri olan bir tahmin bir matrixin set türünde ortaya çıkabilir.

I am not a mathematician so I am not sure if my translation makes sense. If it does I can translate the rest. 

 

 



Edited (11/20/2016) by gokuyum
Edited (11/20/2016) by gokuyum

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