  In this paper, a practical estimation method for a regression model is
proposed using semiparametric efficient score functions applicable to data with
various shapes of errors. First, I derive semiparametric efficient score
vectors for a homoscedastic regression model without any assumptions of errors.
Next, the semiparametric efficient score function can be modified assuming a
certain parametric distribution of errors according to the shape of the error
distribution or by estimating the error distribution non-parametrically.
Nonparametric methods for errors can be used to estimate the parameters of
interest or to find an appropriate parametric error distribution. In this
regard, the proposed estimation methods utilize both parametric and
nonparametric methods for errors appropriately. Through numerical studies, the
performance of the proposed estimation methods is demonstrated.
