Least-Squares Variance Component Estimation Theory and GPS Applications

@inproceedings{AmiriSimkooei2007LeastSquaresVC,
  title={Least-Squares Variance Component Estimation Theory and GPS Applications},
  author={Alireza Amiri-Simkooei},
  year={2007}
}
Data processing in geodetic applications often relies on the least-squares method, for which one needs a proper stochastic model of the observables. Such a realistic covariance matrix allows one first to obtain the best (minimum variance) linear unbiased estimator of the unknown parameters; second, to determine a realistic precision description of the unknowns; and, third, along with the distribution of the data, to correctly perform hypothesis testing and assess quality control measures such… CONTINUE READING
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