The non-stationary gamma process is a non-decreasing stochastic process with independent increments. By this monotonic behavior this stochastic process serves as a natural candidate for modelling time-dependent phenomena such as degradation. In condition-based maintenance the first time such a...

In this report a support system for predicting end prices on eBay is proposed. The end price predictions are based on the item descriptions found in the item listings of eBay, and on some numerical item features. The system uses text mining and boosting algorithms from the field of machine...

Empirical analysis of individual response behavior is sometimes limited due to the lack of explanatory variables at the individual level. In this paper we put forward a new approach to estimate the effects of covariates on individual response, where the covariates are unknown at the individual...

Given a set of timetabled tasks, the multi-depot vehicle scheduling problem is a well-known problem that consists of determining least-cost schedules for vehicles assigned to several depots such that each task is accomplished exactly once by a vehicle. In this paper, we propose to compare the...

Marketing problems often involve inary classification of customers into ``buyers'' versus ``non-buyers'' or ``prefers brand A'' versus ``prefers brand B''. These cases require binary classification models such as logistic regression, linear, and quadratic discriminant analysis. A promising...

Abstract In De Boer (2006) the additive decomposition of the aggregate change in a variable into its factors was considered. I proposed to use the "ideal" Montgomery decomposition, developed in index number theory, rather than the commonly used methods in structural decomposition analysis and...

To minimize the primal support vector machine (SVM) problem, we propose to use iterative majorization. To do so, we propose to use it- erative majorization. To allow for nonlinearity of the predictors, we use (non)monotone spline transformations. An advantage over the usual ker- nel approach in...

We propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared with an...

Most models for purchase timing behavior of households do not take into account that many households have regular and non-shopping days. I propose a statistical model for purchase timing that exploits information on the shopping days of households. It delivers forecasts for the number of...

We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators...