OUTLIER DETECTION AND RELIABILITY OF ADJUSTMENT MODELS WITH SINGULAR COVARIANCE MATRICES
OUTLIER DETECTION AND RELIABILITY OF ADJUSTMENT MODELS WITH SINGULAR COVARIANCE MATRICES
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摘要: Up to now, outlier detection and reliability theory are generally based on the regular Gauss-Markov models, in which the covariance matrix of observations is positively definite. For the adjustment models with singular covariance matrix, the statistics for outlier detection are derived by the authors. The corresponding reliability theory is developed. And the application of the theory is demonstrated with a practical example.Abstract: Up to now, outlier detection and reliability theory are generally based on the regular Gauss-Markov models, in which the covariance matrix of observations is positively definite. For the adjustment models with singular covariance matrix, the statistics for outlier detection are derived by the authors. The corresponding reliability theory is developed. And the application of the theory is demonstrated with a practical example.
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