The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its e±ciency while keeping the maximal breakdown...

Mathematics Subject Classification (2000) 62G35 · 62F99

Empirical growth research faces a high degree of model uncertainty. Apart from the neoclassical growth model, many new (endogenous) growth models have been proposed. This causes a lack of robustness of the parameter estimates and makes the determination of the key determinants of growth...

Extreme-value copulas arise as the possible limits of copulas of componentwise maxima of independent, identically distributed samples.The use of bivariate extreme-value copulas is greatly facilitated by their representation in terms of Pickands dependence functions.The two main families of...

Microeconomic surveys are usually subject to the problem of item nonresponse, typically associated with variables like income and wealth, where confidentiality and/or lack of accurate information can affect the response behavior of the individual. Follow up categorical questions can reduce item...

Multiple quantile plots provide a powerful graphical method for comparing the distributions of two or more populations. This paper develops a method of visualizing triple quantile plots and their associated confidence tubes, thus extending the notion of a QQ plot to three dimensions. More...

Inventory models need some specification of the distribution of demand in order to find the optimal order-up-to level or reorder point.This distribution is unknown in real life and there are several solutions to overcome this problem.One approach is to assume a distribution, estimate its...

AMS classifications: 62G05; 62G07; 62G08; 62G20; 62G32;

Many estimation methods of truncated and censored regression models such as the maximum likelihood and symmetrically censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semipara- metric general trimmed estimator (GTE) of...