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Error Estimation of New Geoid Models: Parameter & Covariance Analysis

This study by C.C. Tscherning from the University of Copenhagen in 2005 focuses on estimating errors in new geoid models. The parameters and associated error estimates are crucial for understanding mean sea surface heights and geoid heights. Parameter estimation techniques, a priori weight matrices, error covariance estimates, and mean square errors are discussed. This research provides insights into computing error estimates for different distances in geoid modeling.

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Error Estimation of New Geoid Models: Parameter & Covariance Analysis

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  1. ARCGICE WP 2.2 ERROR ESTIMATION OF NEW GEOID C.C.Tscherning, University of Copenhagen, 2005-03-01 1

  2. Parameter and error-estimation Observations: • Parameter is equal to N0 mean sea surface height • Ai = 1 if bias only • for all values of i which are associated with geoid heights. C.C.Tscherning, University of Copenhagen, 2005-01-13 2

  3. Parameter estimate • Then an estimate of T and of the parameters X are obtained as • where W is the a-priori weight matrix for the parameters (Generally the zero matrix). C.C.Tscherning, University of Copenhagen, 2005-01-13 3

  4. Error-estimates • The associated error estimates are with • the mean square error of the parameter vector • and the mean square error of an estimated quantity . • Can be computed for different distances C.C.Tscherning, University of Copenhagen, 2005-01-13 4

  5. Error-covariance estimates • The associated error covariance estimates are with • Equal to. C.C.Tscherning, University of Copenhagen, 2005-01-13 5

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