Standard discriminant analysis supposes that both the training sample and the test sample are derived from the same population. When these samples arise from populations differing in their descriptive parameters, a generalization of discriminant analysis consists of adapting the classification...

With income distributions it is common to encounter the problem of missing data. When a parametric model is fitted to the data, the problem can be overcome by specifying the marginal distribution of the observed data. With classical methods of estimation such as the maximum likelihood (ML) an...

The present method allows to detect outlying observations in data which may be described by a deterministic function plus a stochastic component. This type of functional relationship often occurs in experimental data, in toxicological research, for instance. The Hampel identifier, an outlier...