Finite mixture modeling approach is widely used for the analysis of bimodal or multimodal data that are individually observed in many situations. However, in some applications, the analysis becomes substantially challenging as the available data are grouped into categories. In this work, we...

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...

The Markov chain model (MCM) has become a popular tool in the agricultural economics literature to study the impact of various drivers on the structural change of farms, including public support. In order to relax the process-homogeneity assumption underlying the MCM, we consider a mixture of...

The internal estimates of Loss Given Default (LGD) must reflect economic downturn conditions, thus estimating the “downturn LGD”, as the new Basel Capital Accord Basel II establishes. We suggest a methodology to estimate the downturn LGD distribution to overcome the arbitrariness of the...