The article is devoted to the problem of detecting heteroscedasticity in the remnants of the regression model, estimated using the method of least squares. A well-known procedure for the Glaser test is considered, which assumes the construction of auxiliary dependencies of moduli of regression residuals on transformations of independent variables. Parametric estimates and determination criteria for auxiliary regressions in the case of standardized regression estimation are found. The results obtained allowed us to formulate the Glaser test procedure for a given scenario as a task of partial-Boolean linear programming.
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