Tail index estimation depends for its accuracy on a precise choice of the sample fraction, i.e. the number of extreme order statistics on which the estimation is based. A complete solution to the sample fraction selection is given by means of a two step subsample bootstrap method. This method...

We present the Lagrange multiplier rule, one of the basic optimization methods, in a new way. Novel features include: • Explanation of the true source of the power of the rule: reversal of tasks, but not the use of multipliers. • A natural proof based on a simple picture, but not the usual...

Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that encompasses a range of dynamics in the stochastic cycle. This allows for...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

In this paper we consider a two level decentralized distribution system, consisting of one warehouse and N retailers. The warehouse and each retailer follows each his own (s,nQ) order policy. We extended the models as known in the literature to compound renewal demand.

In this paper neural networks are fitted to the real exchange rates of seven industrialized countries. The size and topology of the used networks is found by reducing the size of the network through the use of multiple correlation coefficients, principal component analysis of residuals and...

We propose a new model to describe consideration, consisting of a multivariate probit model component for consideration and a multinomial probit model component for choice, given consideration. The approach allows one to analyze stated consideration set data, revealed consideration set (choice)...

Generalized linear modelling (GLM) is a versatile technique, which may be viewed as a generalization of well-known techniques such as least squares regression, analysis of variance, loglinear modelling, and logistic regression. In may applications, low-order interaction (such as bivariate...

Macroeconomic forecasting is not an easy task, in particular if future growth rates are forecasted in real time. This paper compares various methods to predict the growth rate of US Industrial Production (IP) and of the Composite Coincident Index (CCI) of the Conference Board, over the coming...

This paper examines the issue of coercive journal self citations and the practical usefulness of two recent journal performance metrics, namely the Eigenfactor score, which may be interpreted as measuring “Journal Influence”, and the Article Influence score, using the Thomson Reuters ISI Web...