Covariate Classification Using Dependent Samples

The two-population classification problem using dependent samples is extended when covariates are available for classification. Analysis is done using a conditional model, under a multivariate normal set-up, given the covariates. The conditional model considered here includes the parameter structure relevant to growth models. Likelihood ratio or plug-in likelihood ratio classification rules are derived depending on the knowledge of the parameters in the model. For exact distribution of the classification statistics, they are reduced to forms suitable for application of standard results.