A dimension reduction method for model-based clustering via a finite mixture of shifted asymmetric Laplace distributions is introduced. The approach is based on existing work within the Gaussian paradigm and relies on identification of a reduced subspace. This subspace contains linear...

We derive some general results on the Fisher information (FI) contained in the data obtained from the ranked set sampling (RSS) design relative to its counterpart under the simple random sampling (SRS) for a finite mixture model. We propose different variations of RSS data and show how to...

A statistical process control chart named the mixture cumulative count control chart (MCCC-chart) is suggested in this study, motivated by an existing control chart named cumulative count control chart (CCC-chart). The MCCC-chart is constructed based on the distribution function of a two...

We investigate to what extent convergence in production levels per worker has been achieved in Germany since unification. To this end, we model the distribution of GDP per employee across German districts using two-component normal mixtures. While in the first year after unification, the...

Semi-supervised classification can help to improve generative classifiers by taking into account the information provided by the unlabeled data points, especially when there are far more unlabeled data than labeled data. The aim is to select a generative classification model using both unlabeled...

The Internal Ratings Based (IRB) approach introduced in the Basel II Accord requires financial institutions to estimate not just the probability of default, but also the Loss Given Default (LGD), i.e., the proportion of the outstanding loan that will be lost in the event of a default. However,...