The article explores tests for the error distribution in linear and nonparametric regression models. The researchers used the parametric bootstrap method to address the issue of non-distribution-free tests. Their findings show that the parametric bootstrap test is reliable and accessible, providing a solution for testing assumptions about error distribution in these models, even with moderate sample sizes.