Nichtparametrische Verfahren zur Dichte- und Regressionsschätzung setzen die Wahl eines Glättungsparameters voraus. Ein oft verwendetes Verfahren zu dessen Bestimmung ist die Kreuzvalidierung. Die Übertragung dieser Methode auf die Quantiisregression ist Gegenstand der vorliegenden Arbeit. Es...

There are various parametric models to analyse the volatility in time series of financial market data. For maximum likelihood estimation these parametric methods require the assumption of a known conditional distribution. In this paper we examine the conditional distribution of daily DAX returns...

In diesem Aufsatz wird die nichtparametrische Autoregression auf die Prognose von Quantilen angewendet. Verfahren der Kernregression werden benutzt, um zu autoregressiven Quantiisschätzern zu gelangen. Da die üblichen Maße zur Beurteilung der Prognose, wie etwa der mittlere quadratische...

A three parameter (location, scale, shape) generalization of the logistic distribution is fitted to data. Local maximum likelihood estimators of the parameters are derived. Although the likelihood function is unbounded, the likelihood equations have a consistent root. ML-estimation combined with...

To estimate cell probabilities for ordered sparse contingency tables several smoothing techniques have been investigated. It has been recognized that nonparametric smoothing methods provide estimators of cell probabilities that have better performance than the pure frequency estimators. With the...

The procedures of estimating prediction intervals for ARMA processes can be divided into model based methods and empirical methods. Model based methods require knowledge of the model and the underlying innovation distribution. Empirical methods are based on the sample forecast errors. In this...