Göran Kauermann

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This article describes the asymptotic properties of local polynomial regression estimators for univariate and additive models when observation weights are included. The implications of these ndings are discussed for local scoring estimators, a widely used class of estimators for generalized additive models described in Hastie and Tibshirani (1990).
This article presents a modified Newton method for minimizing multidi-mensional bandwidth selection for estimation in generalized additive models. The method is based on the Generalized Cross-Validation criterion applied to backfitting estimates. The approach in particular is applicable to higher dimensional problems and provides a computationally efficient(More)
The paper discusses asymptotic properties of penalized spline smoothing if the spline basis increases with the sample size. The proof is provided in a generalized smoothing model allowing for non-normal responses. The results are extended in two ways. First, assuming the spline coefficients to be a priori normally distributed links the smoothing framework(More)
Multi-phase surveys are often conducted in forestry, with the goal of estimating tree characteristics and volume over large regions. Design-based estimation of such q u a n tities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from remote sensing. The exact(More)
The paper considers smooth modelling of hazard functions, where dynamics is modelled in both, duration time and calendar time. The model is specified with time dynamic covariate effects to replace restrictive assumptions of proportional hazards. Additivity of the time effects is assumed which allows for simple estimation in a backfitting style. Penalized(More)
Survival data are often modelled by the Cox proportional hazards model, which assumes that covariate effects are constant over time. In recent years however, several new approaches have been suggested which allow covariate effects to vary with time. Non-proportional hazard functions, with covariate effects changing dynamically, can be fitted using penalised(More)