Książka Variance component estimation in linear models AliReza Amiri-Simkooei

Variance component estimation in linear models

Język: Angielski
Oprawa: Miękka
Wydawca: VDM Verlag
Dostępność: Dostępna u dostawcy
Wysyłamy za 14-21 dni
341.27
Data processing in many fields of applications often relies on the least-squares method, for which a...

Informacje o książce

Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2010
strony
252
EAN
9783639268515
ISBN
3639268512
Enbook ID
06834139
Wydawca
Waga
372
Wymiary
152 x 229 x 14

Pełny opis

Data processing in many fields of applications often relies on the least-squares method, for which a realistic stochastic model of the observables is needed. The estimation of the unknown (co)variance components is generally referred to as variance component estimation (VCE). A review of the existing VCE methods such as MINQUE, BIQUE, and REML is given, and the method of least-squares variance component estimation is in particular discussed. Theoretical and practical aspects of the method are elaborated. In the theoretical viewpoint, an important feature of the method is the capability of applying hypothesis testing to the stochastic model. One can then find an appropriate structure of the stochastic model which includes the relevant noise components into the covariance matrix. In the practical viewpoint, the application of the method to the global positioning system (GPS) observables is presented. Issues like time-correlated noise, satellite elevation dependence, and correlation between different observation types are of particular interest.

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