Göran Kauermann

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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)
In regression scenarios there is a growing demand for information on the conditional distribution of the response beyond the mean. In this scenario quantile regression is an established method of tail analysis. It is well understood in terms of asymptotic properties and estimation quality. Another way to look at the tail of a distribution is via expectiles.(More)
Multi-phase surveys are often conducted in forest inventory, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information(More)
SUMMARY We devise a classification algorithm based on generalised linear mixed model (GLMM) technology. The algorithm incorporates spline smoothing, additive model-type structures and model selection. For reasons of speed we employ the Laplace approximation, rather than Monte Carlo methods. Tests on real and simulated data show the algorithm to have good(More)