We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...

Prediction of demand for professional sports is increasingly drawing the attention of economists. We apply linear mixed models for modeling attendance figures at Spanish professional football. We investigate economic variables, such as the price of the tickets or the size of the market, and...

Im Rahmen des Projektes ?Zeitreihenanalytische Methoden zur Behandlung von Online-Monitoring-Daten aus der Intensivmedizin? im Sonderforschungsbereich 475 wird eine klinische Studie zur Evaluierung und zum Vergleich von Alarm-Algorithmen für die Patientenüberwachung auf Intensivstationen...

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable...

Small area estimation is studied under a spatio-temporal Fay–Herriot model. Model fitting based on restricted maximum likelihood is described and empirical best linear unbiased predictors are derived under the model. A parametric bootstrap procedure is proposed for the estimation of the mean...

Estimation of small area means under a basic area level model is studied, using an empirical Bayes (best) estimator or a weighted estimator with fixed weights. Mean squared errors (MSEs) of the estimators and nearly unbiased (or exactly unbiased) estimators of MSE are derived under three...