Variance component estimation in linear models

Name: Variance component estimation in linear models
Brand: VDM Verlag
SKU: 9783639268515
Price: 437.07 RON
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Autor: AliReza Amiri-Simkooei

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Editura: VDM Verlag

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Data processing in many fields of applications often relies on the least-squares method, for which a...

Informații despre carte

Autor

AliReza Amiri-Simkooei

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

252

EAN

9783639268515

ISBN

3639268512

Enbook ID

06834139

Editura

VDM Verlag

Greutate

372

Dimensiuni

152 x 229 x 14

Descriere completă

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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Variance component estimation in linear models

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