Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M : H H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate the zero point o H of M. These procedures work in appropriate finite dimensional sub-spaces of...

ExpEnd is a Gauss programme for non-linear generalised method of moments (GMM) estimation of exponential models with endogenous regressors for cross section and panel data. The estimators included in this package are simple Poisson pseudo ML; GMM for cross section data using moment conditions...

For a broad class of nonlinear regression models we investigate the locally E- and c-optimal design problem. It is demonstrated that in many cases the optimal designs with respect to these optimality criteria are supported at the Chebyshev points, which are the local extrema of the...

This paper analyses a class of nonlinear time series models exhibiting long memory. These processes exhibit short memory fluctuations around a local mean (regime) which switches randomly such that the durations of the regimes follow a power law. We show that if a large number of independent...

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run and are obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...

Die Arbeit umfaßt die Darstellung und Anwendung von Regressionsmodellen für Zähldaten, deren abhängige Variable nur nichtnegative ganzzahlige Werte annehmen kann. Die Spezifikationen des Poisson- und des NegBin 2-Modells mit den zugehörigen Schätzverfahren und Beurteilungskriterien werden...

Consider estimating the mean of a normal distribution with known variance, when that mean is known to lie in a bounded interval. In a decision-theoretic framework we study finite sample properties of a class of nonlinear' estimators. These estimators are based on thresholding techniques which...