Bielefeld University

About: Bielefeld University is a education organization based out in Bielefeld, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Quantum chromodynamics. The organization has 10123 authors who have published 26576 publications receiving 728250 citations. The organization is also known as: University of Bielefeld & UNIVERSITAET BIELEFELD.

Characterization of model sets by dynamical systems

Abstract: It is shown how regular model sets can be characterized in terms of the regularity properties of their associated dynamical systems. The proof proceeds in two steps. First, we characterize regular model sets in terms of a certain map $\beta$ and then relate the properties of $\beta$ to those of the underlying dynamical system. As a by-product, we can show that regular model sets are, in a suitable sense, as close to periodic sets as possible among repetitive aperiodic sets.

A comparison of big-five structures of personality traits in Dutch, English, and German

Abstract: We compare Big-Five factor structures found in Dutch, American English, and German, and present a joint structure. The data consist of self- and peer ratings of 600 subjects with 551 Dutch trait-descriptive adjectives, 636 subjects with 540 English adjectives, and 802 subjects with 430 German adjectives. On the basis of 126 common items, we assess the congruences between the factors as originally published, as resulting from target rotations, and from simultaneous rotations. With the exception of the Dutch Factor V, the Big-Five factors recur across languages in a relative but not in a strict sense. Moreover, at a more detailed level differences in the positions of the axes are uncovered. By applying a split-sample technique to the three data sets, we verify that these differences do not arise through unreliability. Also, few trait terms appear to have the same precise meaning across these three languages; such labels therefore cannot serve as anchor concepts for an international language of personality. (C) 1997 by John Wiley & Sons, Ltd.

Fast adaptive penalized splines

Abstract: This article proposes a numerically simple method for locally adaptive smoothing. The heterogeneous regression function is modeled as a penalized spline with a varying smoothing parameter modeled as another penalized spline. This is formulated as a hierarchical mixed model, with spline coefficients following zero mean normal distribution with a smooth variance structure. The major contribution of this article is to use the Laplace approximation of the marginal likelihood for estimation. This method is numerically simple and fast. The idea is extended to spatial and non-normal response smoothing.