In statistical practice multicollinearity of predictor variables is rather the rule than the exception and appropriate models are needed to avoid instability of predictions. Feature extraction methods reflect the idea that latent variables not measurable directly are underlying the original...

In this paper we propose a simulation study in order to discuss four statistical models dealing with the problem of parameter estimation in enzyme-kinetics. The pseudo-maximumlikelihood estimators for the transform-both-sides-model and the weighted TBS-model are compared with...

In this paper we use 4 different time series models to forecast sales in a goods management system. We use a variety of forecast combining techniques and measure the forecast quality by applying symmetric and asymmetric forecast quality measures. Simple, rank-, and criteria-based combining...

In this paper we consider the asymptotic distribution of S -estimators in the nonlinear regression model with long-memory error terms. S - estimators are robust estimates with a high breakdown point and good asymptotic properties in the i.i.d case. They are constructed for linear regression. In...

In this paper we introduce the STAR-STGARCH model that can characterizenonlinear behaviour both in the conditional mean and the conditionalvariance. A modelling cycle for this family of models, consisting ofspecification, estimation, and evaluation stages is constructed.Misspecification tests...