A robustness study of student-t distributions in regression models with application to infant birth weight data in Indonesia

Abstract

In regression models, the use of least squares method may not appropriate in modelling the data containing outliers. Many robust statistical methods have been developed to handle such a problem. Lange et al. [1] developed robust models based on t distributions and using M-estimation approaches. In this recent article we evaluate the performance of M-estimation as well as investigated the robustness of t distribution models in linear regression by means of simulation. The models are then applied to infant birth-weight data in Indonesia. We show that the t distribution models with small degrees of freedoms have produced better estimates from perspectives of their performance and robustness when compared to other estimates.