Latent variable models are used for analyzing multivariate data. Recently, generalized linear latent variable models for categorical, metric, and mixed-type responses estimated via maximum likelihood (ML) have been proposed. Model deviations, such as data contamination, are shown analytically,...

A risk management strategy that is designed to be robust to the Global Financial Crisis (GFC), in the sense of selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models, was proposed in McAleer et al. (2010c). The robust forecast is based on the median of the...

A reasonable result from a complex simulation does not imply validity of the underlying formulations: robustness checks are essential. We analyze the disturbance scheme for solder joint lifetime prediction from this viewpoint and results suggest it may not provide the previously reported...

Recent research on robust decision aiding has focused on identifying a range of recommendations from preferential information and the selection of representative models compatible with preferential constraints.This study presents an experimental analysis on the relationship between the results...