In stationary point process theory, the concept Palm distribution plays an important role.Many important results (like for instance Little s law, so important in many fields) arise from it.However, in the non-stationary case a whole family of local Palm distributions (PD s) has to be considered...

Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integervalued phenomena that evolve in time.The distribution of an INAR(p) process is determined by two parameters: a vector of survival probabilities and a probability distribution on the nonnegative...

This paper considers integer-valued autoregressive processes where the autoregression parameter is close to unity.We consider the asymptotics of this `near unit root' situation.The local asymptotic structure of the likelihood ratios of the model is obtained, showing that the limit experiment is...

The paper discusses the problem of a fallible auditor who assesses the values of sampled records, but may make mistakes.To detect these mistakes, a subsample of the checked elements is checked again, now by an infallible expert. We propose a model for this kind of double check, which takes into...

Multivariate regression is discussed, where the observations of the dependent variables are (monotone) missing completely at random; the explanatory variables are assumed to be completely observed.We discuss OLS-, GLS- and a certain form of E(stimated) GLS-estimation.It turns out that...

In this paper we investigate global optimization for black-box simulations using metamodels to guide this optimization. As a novel metamodel we introduce intrinsic Kriging, for either deterministic or random simulation. For deterministic simulation we study the famous `efficient global...

Kriging is a popular method for estimating the global optimum of a simulated system. Kriging approximates the input/output function of the simulation model. Kriging also estimates the variances of the predictions of outputs for input combinations not yet simulated. These predictions and their...

The three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian and Prucha (2007), which corrects for spatially correlated errors in static panel data models, is extended by introducing fixed effects, a spatial lag, and a one-period lag of the dependent variable as additional...