2000/05/28 by Alekhin Sergey, Sergey, Alekhin
Computer Science · Engineering · Physics and Astronomy · #FOS: Physical sciences #GNSS positioning and interference #High Energy Physics - Experiment (hep-ex) #Scientific Research and Discoveries #Target Tracking and Data Fusion in Sensor Networks #hep-ex
paper · pdf · doi:10.48550/arxiv.hep-ex/0005042
12 pages, LATEX, 2 figures (EPS)
arxiv created 2000/05/28 · openalex publication_date 2000/05/28 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The statistical properties of estimator using covariance matrix for the account of point-to-point correlations due to systematic errors are analyzed. It is shown that the covariance matrix estimator (CME) is consistent for the realistic cases (when systematic errors on the fitted parameters are not extremely large comparing with the statistical ones) and its dispersion is always smaller, than the dispersion of the simplified χ2 estimator applied to the correlated data. The CME bias is negligible for the realistic cases if the covariance matrix is calculated during the fit iteratively using the parameter estimator itself. Analytical formula for the covariance matrix inversion allows to perform fast and precise calculations even for very large data sets. All this allows for efficient use of the CME in the global fits.