The problem of calculating the uncertainty bands for a linear regression with correlated initial data is considered. The conformance factors for regression uncertainty bands with different models of errors in the initial data are obtained by the Monte-Carlo method. The linear regression coefficients are estimated by the generalized method of least squares. The following models of measurement error are considered: Gaussian white noise, exponentially correlated noise, and flicker noise. A comparative analysis of the uncertainty bands of linear drift is conducted for these models.
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Translated from Izmeritel’naya Tekhnika, No. 5, pp. 21–24, May, 2019.
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Stepanov, A.V., Chunovkina, A.G. Estimation of Conformance Bands for Linear Regression with Correlated Input Data. Meas Tech 62, 410–414 (2019). https://doi.org/10.1007/s11018-019-01638-6
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DOI: https://doi.org/10.1007/s11018-019-01638-6