Huang, Wentao; Pao, Kuanmin Minimum distance estimations in a switching regression model. (English) Zbl 0728.62065 Int. J. Inf. Manage. Sci. 2, No. 1, 119-128 (1991). Summary: We propose minimum distance estimators of parameters in a switching regression model under parametric error distributions with Cramér-von Mises type discrepancy. The main results of the proposed minimum distance estimator \({\hat \eta}=({\hat \beta}_ 1,{\hat \beta}_ 2,\hat p,{\hat \theta}_ 1,{\hat \theta}_ 2)\) of \(\eta =(\beta_ 1,\beta_ 2,p,\theta_ 1,\theta_ 2)\) show that (i) \({\hat \eta}\) is a strongly consistent estimator of \(\eta\), (ii) the limiting distribution of \(\sqrt{n}({\hat \eta}-\eta)\) is 5-variate normal. MSC: 62J05 Linear regression; mixed models 62E20 Asymptotic distribution theory in statistics 62F12 Asymptotic properties of parametric estimators Keywords:strong consistency; asymptotic normality; minimum distance estimators; switching regression model; Cramér-von Mises type discrepancy; limiting distribution PDFBibTeX XMLCite \textit{W. Huang} and \textit{K. Pao}, Int. J. Inf. Manage. Sci. 2, No. 1, 119--128 (1991; Zbl 0728.62065)