Abstract
The problem of constructing linear regression models in the presence of errors in input and output data is considered. A statistical test for detecting measurement errors in input data is proposed that does not require a preliminary consistent estimation of the coefficients under the assumption of the presence of errors. The test is validated by Monte-Carlo statistical simulation.
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