BOOTSTRAPPING FINITE MIXTURE MODELS
Bettina Gr, Friderich Leisch · 2004
COMPSTAT 2004 section: Clustering, Resampling methods. Abstract: Finite mixture regression models are used for modelling unob- served heterogeneity in the population. However, depending on the specii- cations these models need not be identiiable, which is especially of concern if the parameters are interpreted. As bootstrap methods are already used as a diagnostic tool for linear regression models, we investigate their use for inite mixture models. We show that bootstrapping helps in revealing identiiability problems and that parametric bootstrapping can be used for analyzing the reliability of coe cient estimates.