Bernhard Klar

A spot market model for pricing derivatives in electricity markets

Abstract In this paper, we analyse the evolution of prices in deregulated electricity markets. We present a general model that simultaneously takes into account the following features: seasonal patterns, price spikes, mean reversion, price dependent volatilities and long term non-stationarity. We estimate the parameters of the model using historical data from the European Energy Exchange. Finally, we demonstrate how it can be used for pricing derivatives via Monte Carlo simulation.

Comparing the effects of mobile computers and traditional approaches in environmental education

Environmental education and computers? That was traditionally seen as an antagonism. But environmental educators who compete for attention and face new challenges in an age of mobile devices, have begun to explore the opportunities that mobile computers may offer in supporting environmental learning experiences. This study investigates the impact of a mobile guide system on different parameters of environmental literacy in comparison to traditional instruments of environmental education (i.e. brochure, human guide). In a field experiment at a floodplain conservation site, 185 school children and 76 adults participated in a guided tour using different media. Despite the novelty of mobile devices and usability issues associated with the prototype mobile nature guide, participants using the computer-assisted medium achieved similar results concerning environmental literacy components. The computer as mobile guide can lead to an increase in environmental knowledge and in case of the children it can increase their motivation to engage in environmental education activities.

Visual and statistical comparison of metagenomes

BACKGROUND Metagenomics is the study of the genomic content of an environmental sample of microbes. Advances in the through-put and cost-efficiency of sequencing technology is fueling a rapid increase in the number and size of metagenomic datasets being generated. Bioinformatics is faced with the problem of how to handle and analyze these datasets in an efficient and useful way. One goal of these metagenomic studies is to get a basic understanding of the microbial world both surrounding us and within us. One major challenge is how to compare multiple datasets. Furthermore, there is a need for bioinformatics tools that can process many large datasets and are easy to use. RESULTS This article describes two new and helpful techniques for comparing multiple metagenomic datasets. The first is a visualization technique for multiple datasets and the second is a new statistical method for highlighting the differences in a pairwise comparison. We have developed implementations of both methods that are suitable for very large datasets and provide these in Version 3 of our standalone metagenome analysis tool MEGAN. CONCLUSION These new methods are suitable for the visual comparison of many large metagenomes and the statistical comparison of two metagenomes at a time. Nevertheless, more work needs to be done to support the comparative analysis of multiple metagenome datasets. AVAILABILITY Version 3 of MEGAN, which implements all ideas presented in this article, can be obtained from our web site at: www-ab.informatik.uni-tuebingen.de/software/megan. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Invariant tests for symmetry about an unspecified point based on the empirical characteristic function

This paper considers a flexible class of omnibus affine invariant tests for the hypothesis that a multivariate distribution is symmetric about an unspecified point. The test statistics are weighted integrals involving the imaginary part of the empirical characteristic function of suitably standardized given data, and they have an alternative representation in terms of an L2-distance of nonparametric kernel density estimators. Moreover, there is a connection with two measures of multivariate skewness. The tests are performed via a permutational procedure that conditions on the data.

BOUNDS ON TAIL PROBABILITIES OF DISCRETE DISTRIBUTIONS

We examine several approaches to derive lower and upper bounds on tail probabilities of discrete distributions. Numerical comparisons exemplify the quality of the bounds.

Goodness-of-Fit Tests for the Inverse Gaussian Distribution Based on the Empirical Laplace Transform

This paper considers two flexible classes of omnibus goodness-of-fit tests for the inverse Gaussian distribution. The test statistics are weighted integrals over the squared modulus of some measure of deviation of the empirical distribution of given data from the family of inverse Gaussian laws, expressed by means of the empirical Laplace transform. Both classes of statistics are connected to the first nonzero component of Neymans smooth test for the inverse Gaussian distribution. The tests, when implemented via the parametric bootstrap, maintain a nominal level of significance very closely. A large-scale simulation study shows that the new tests compare favorably with classical goodness-of-fit tests for the inverse Gaussian distribution, based on the empirical distribution function.

Tests for normal mixtures based on the empirical characteristic function

A goodness-of-fit test for two-component homoscedastic and homothetic mixtures of normal distributions is proposed. The tests are based on a weighted L2-type distance between the empirical characteristic function and its population counterpart, where in the latter, parameters are replaced by consistent estimators. Consequently, the resulting tests are consistent against general alternatives. When moment estimation is employed and as the decay of the weight function tends to infinity the test statistics approach limit values, which are related to the first nonvanishing moment equation. The new tests are compared via simulation to other omnibus tests for mixtures of normal distributions, and are applied to several real data sets.

Interaction between cadmium exposure and infection with the intestinal parasite Moniliformis moniliformis (Acanthocephala) on the stress hormone levels in rats

The impact of an infection with the acanthocephalan Moniliformis moniliformis and a simultaneous Cd-exposure on the stress hormone levels of rats was studied. Immediately after the application of cadmium to some rats, cortisol levels in all groups of rats, as quantified by radioimmunoassay (RIA), significantly increased. However, infections with M. moniliformis as well as the uptake of Cd reduced significantly the cortisol release compared to untreated controls. While catecholamine concentrations, as determined by high-performance liquid chromatography (HPLC), showed no clear tendency during the experimental period, the ratio of C(adrenaline)/C(noradrenaline) in the controls showed the significantly lowest value of all four groups after killing the animals. Thus, the acanthocephalan infection as well as the Cd-exposure and the combination of both treatments affect hormone homeostasis in the rats which probably lead to negative effects on the health of the rat. Therefore parasite infections must be carefully considered in environmental impact studies, as an important factor affecting the hosts health.

A class of tests for exponentiality against HNBUE alternatives

This paper presents tests of exponentiality against HNBUE alternatives. The new class of test statistics is based on the difference between the integrated distribution function and its empirical counterpart. As special cases, the class includes the asymptotically most powerful test for exponentiality against the Makeham alternative and the first nonzero component of Neymans smooth test of fit for the exponential distribution.

Diagnostic smooth tests of fit

Abstract. Smooth tests are frequently used for testing the goodness of fit of a parametric family of distributions. One reason for the popularity of the smooth tests are the diagnostic properties commonly attributed to them. In recent years, however, it has been realized that these tests are strictly non-diagnostic when used conventionally. The paper examines how the smooth test statistics must be rescaled in order to obtain procedures having diagnostic properties at least for large sample sizes.