Summary: The aim of this paper is to investigate a semiparametric regression model with \(\varphi\) mixing and \(\psi\) mixing errors. The methods of least squares and weight functions are used to define the estimators \(\beta_{m,n}\) and \(g_{m,n} (x)\) for the unknown parameter \(\beta\) and the unknown function \(g\), respectively. Strong consistency and the moment consistency for these estimators are proved under some weaker conditions by using moment inequalities of mixing sequences and properties of convex functions, which generalize the mentioned results.