Robust mixture regression model fitting by Laplace distribution

A robust estimation procedure for mixture linear regression models is proposed by assuming that the error terms follow a Laplace distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the Laplace distribution is a scale mixture of a normal distribution. Finite sample performance of the proposed algorithm is evaluated by numerical simulation studies. The superiority of the proposed method is illustrated by some comparison studies with other existing procedures in the literature. A real data example is also included to illustrate the application of the proposed method. MSC: primary 62F35; secondary 62F10