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ÖLÇÜM HATALI LiNEER OLMAYAN MODELLER ve EN KÜÇÜK KARELER KESTİRİMİ

The Nonlinear Models with Measurement Error and Least Squares Estimation

Journal Name:

  • Dicle Üniversitesi Ziya Gökalp Eğitim Fakültesi Dergisi

Publication Year:

  • 2005

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this study , it has been purposed to estimate parameters of nonlineer regression model Y=f(x;  ) with functional relationships, where Yt and Xt are both subject to measurement error , when we consider observe ( Yt , Xt ) for t t t t t z Y  y  e , X  x  u and t  1,2,...,n there for it is assumed that the error vector ( , )' t t t   e u has zero mean value and covariance error matrix  with normal distibuted , that is positive defined and nonsinguler . In cases whether covariance error matrix  known or unknown, we give least squares estimation about y f (x; ) t  that depend on diferantation .
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Abstract (Original Language): 
Bu çalışmada, t t t t t z Y  y  e , X  x  u ve t  1,2,...,n için ( , ) t t Y X gözlemleri yapıldığında, ölçüm hatalı lineer olmayan Y=f(x; ) fonksiyonel ilişkisine sahip regresiyon modelinin parametreleri ( , )' t t t   e u hata vektörünün sıfır ortalamaya ve pozitif tanımlı singuler olmayan  kovaryans hata matrisi ile normal dağılıma sahip olduğunu kabul ederek  hata matrisinin bilindiği veya bilinmediği durumlarda y f (x; ) t  ’nin tamamen türeve dayalı en küçük kareler kestirimi incelenmiştir.
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  • 1
107-113
  • Turkish

REFERENCES

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