The notion of transit function is introduced to present a unifying approach for results and ideas on intervals, convexities and betweenness in graphs and posets. Prime examples of such transit functions are the interval function I and the induced path function J of a connected graph. Another...

Increased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present stochastic programming based approaches by which a deterministic location...

For testing whether a distribution function is heavy tailed, we study the Kolmogorov test, Berk-Jones test, score test and their integrated versions. A comparison is conducted via Bahadur efficiency and simulations. The score test and the integrated score test show the best performance. Although...

In Hoogerheide, Kaashoek and Van Dijk (2002) the class of neural network sampling methods is introduced to sample from a target (posterior) distribution that may be multi-modal or skew, or exhibit strong correlation among the parameters. In these methods the neural network is used as an...

In this paper we consider the estimation of probabilistic ranking models in the context of conjoint experiments. By using approximate rather than exact ranking probabilities, we do not need to compute high-dimensional integrals. We extend the approximation technique proposed by...

This paper links judgemental adjustment of model-based forecasts with the potential presence of exceptional observations in time series. Specific attention is given to current and future additive outliers, as these require most consideration. A brief illustration to a quarterly real GDP series...

Purchase timing of households is usually modeled at the category level. Marketing efforts are however only available at the brand level. Hence, to describe category-level interpurchase times using marketing efforts one has to construct a category-level measure of marketing efforts from the...

The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parametrization; and...

We characterize second order regular variation of the tail sum of F together with a balance condition on the tails interms of the behaviour of the characteristic function near zero.

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlo method for Bayesian analysis of models with ill-behaved posterior distributions. In order to sample efficiently from such a distribution, a location-scale transformation and a transformation to polar coordinates are used....