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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)
We introduce an approach based on the recently introduced functional mode analysis to identify collective modes of internal dynamics that maximally correlate to an external order parameter of functional interest. Input structural data can be either experimentally determined structure ensembles or simulated ensembles, such as molecular dynamics trajectories.(More)
The increasing demand for software project managers in industry requires strategies for the development of management-related knowledge and skills of the current and future software workforce. Although several educational approaches help to develop the necessary skills in a university setting, few empirical studies are currently available to characterise(More)
Institutions are a major field of interest in the study of development processes. We contribute to this discussion concentrating our research on political institutions and their effect on the non-income dimensions of human development. First, we elaborate a theoretical argument why and under what conditions democracies compared to autocratic political(More)
This article proposes a simple and fast approach to build simultaneous confidence bands and perform specification tests for smooth curves in additive models. The method allows for handling of spatially heterogeneous functions and its derivatives as well as heteroscedasticity in the data. It is applied to study the determinants of chronic undernutrition of(More)
Tensor-driven anisotropic diffusion and regularisation have been successfully applied to a wide range of image processing and computer vision tasks such as denoising, inpainting, and optical flow. Empirically it has been shown that anisotropic models with a diffusion tensor perform better than their isotropic counterparts with a scalar-valued diffusivity(More)
In this article we discuss estimation of generalized threshold regression models in settings when the threshold parameter lacks identifiability. In particular, if estimation of the regression coefficients is associated with high uncertainty and/or the difference between regimes is small, estimators of the threshold and, hence, of the whole model can be(More)