Challenges in the analyses of growth mixture models include missing data, outliers, estimation, and model selection. Four non-ignorable missingness models to recover the information due to missing data, and three robust models to reduce the effect of non-normality are proposed. A full Bayesian...

It is well known that transformation of the response may improve the homogeneity and the approximate normality of the errors. Unfortunately, the estimated transformation and related test statistic may be sensitive to the presence of one, or several, atypical observations. In addition, it is...

The article illustrates the use of the forward search to provide robust analyses of econometric data. The emphasis is on informative plots that reveal the inferential importance of each observation. The division of observations into “good” and “bad” leverage points is shown to be...

In geostatistics, spatial data will be analysed that often come from irregularly distributed sampling locations. Interest is in modelling the data_ i.e. estimating distributional parameters and then to predict the phenomenon under study at unobserved sites within the corresponding sampling...

In geostatistics, spatial data will be analysed that often come from irregularly distributed sampling locations. Interest is in modelling the data_ i.e. estimating distributional parameters and then to predict the phenomenon under study at unobserved sites within the corresponding sampling...