The extended-least-squares treatment of correlated data

A generalization of the extended-least-squares algorithms for the case of correlated discrepant data is given. The expressions for linear, unbiased, minimum-variance estimators previously derived are reformulated. A posteriori estimates of the variance taking into account the inconsistency of all the experimental data have the same form as in the case of noncorrelated data. These estimates extend the previous improvement on the "traditional" Birge-ratio procedure to the case of correlated input data.<
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