The traditional estimation of mixture regression models is based on the normal assumption of component errors and thus is sensitive to outliers or heavy-tailed errors. A robust mixture regression model based on the t-distribution by extending the mixture of t-distributions to the regression...

Mixture model-based methods assuming independence may not be valid for clustering growth trajectories arising from multilevel studies because longitudinal data collected from the same unit are often correlated. A mixture of mixed effects models is considered to capture the correlation using...

Modelling bias is an important consideration when dealing with inexpert annotations. We are concerned with training a classifier to perform sentiment analysis on news media articles, some of which have been manually annotated by volunteers. The classifier is trained on the words in the articles...