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Michel Talagrand from CNRS in Paris is awarded the Abel Prize 2024 for his work in probability theory and stochastic processes. The prize was awarded by the Norwegian Academy of Sciences and includes a cash prize of 7.5 million Norwegian Kroner. The YAM Network Germany is a collaboration between German excellence clusters and AIMS to provide talented AIMS graduates with the opportunity to study and research in Germany. The network organizes regular events and strengthens the community of YAM scholars. [Extracted from the article]

We present first calculations of critical spectral functions of the relaxational Models A, B, and C in the Halperin-Hohenberg classification using a real-time formulation of the functional renormalization group (FRG). We revisit the prediction by Son and Stephanov that the linear coupling of a conserved density to the non-conserved order parameter of Model A gives rise to critical Model-B dynamics. We formulate both 1-loop and 2-loop self-consistent expansion schemes in the 1PI vertex functions as truncations of the effective average action suitable for real-time applications, and analyze in detail how the different critical dynamics are properly incorporated in the framework of the FRG on the closed-time path. We present results for the corresponding critical spectral functions, extract the dynamic critical exponents for Models A, B, and C, in two and three spatial dimensions, respectively, and compare the resulting values with recent results from the literature. [ABSTRACT FROM AUTHOR]

We consider the class of r -Pareto processes defined on [ 0 , 1 ] whose max-stable counterparts are Brown–Resnick processes. The aim of this paper is to propose a test whether the extreme value index function of a r -Pareto process of this class remains constant over [ 0 , 1 ]. We assume that we observe several independent r -Pareto processes over equispaced grids of [ 0 , 1 ] but with possibly heterogeneous grid resolutions. We build a test based on the normalized approximate total variations of the paths of these processes. We provide its properties under infill asymptotics and assess its finite sample performance through simulation experiments. We discuss how to proceed for random processes that belong to the domain of attraction of Brown–Resnick r -Pareto processes and illustrate the approach with an application to wind speed data from Germany. [ABSTRACT FROM AUTHOR]

This paper provides evidence on the degree of persistence of one of the key components of the CAPM, namely the market risk premium, as well as its volatility. The analysis applies fractional integration methods to data for the US, Germany and Japan, and for robustness purposes considers different time horizons (2, 5 and 10 years) and frequencies (monthly and weekly). The empirical findings in most cases imply that the market risk premium is a highly persistent variable which can be characterized as a random walk process, whilst its volatility is less persistent and exhibits stationary long-memory behaviour. There is also evidence that in the case of the US the degree of persistence has changed as a results of various events; this is confirmed by both endogenous break tests and the associated subsample estimates. Market participants should take this evidence into account when designing their investment strategies. [ABSTRACT FROM AUTHOR]

A fundamental challenge in ecology is to identify the processes which explain how species come to occupy diverse communities. There is uncertainty about whether community composition arises through deterministic processes, whereby trait differences between species make them more or less adapted to certain environmental conditions. We tested the capacity for deterministic processes to explain the long-term dynamics of phytoplankton community structure in Lake Müggelsee—a shallow and eutrophic lake in Berlin, Germany using a trait-based approach. We developed a null model representing random processes alone by generating a time series of random trait distributions derived from the observed long-term data. We determined the extent to which deterministic processes lead to nonrandom patterns in phytoplankton communities by comparing the resulting null-trait distributions with the observed trait distributions in the long-term data. We found that phytoplankton communities fell along a gradient from random to nonrandom trait distributions, suggesting that deterministic processes alone do not fully describe the community structure. Nonrandom patterns were observed in communities with high species richness and during late spring as well as early winter. But neither species richness nor seasonality explained nonrandom patterns consistently for different metrics and traits given the high relevance of random trait distribution patterns. Thus, deterministic and stochastic processes may be needed to fully explain the structure of phytoplankton communities under changing environmental conditions. [ABSTRACT FROM AUTHOR]

• Pairwise coupling of Nataf-based stochastic models through disaggregation. • Generation of multi-scale timeseries with any distribution and correlation structure. • Applicable for multivariate disaggregation/simulation problems. The generation of hydrometeorological time series that exhibit a given probabilistic and stochastic behavior across multiple temporal levels, traditionally expressed in terms of specific statistical characteristics of the observed data, is a crucial task for risk-based water resources studies, and simultaneously a puzzle for the community of stochastics. The main challenge stems from the fact that the reproduction of a specific behavior at a certain temporal level does not imply the reproduction of the desirable behavior at any other level of aggregation. In this respect, we first introduce a pairwise coupling of Nataf-based stochastic models within a disaggregation scheme, and next we propose their puzzle-type configuration to provide a generic stochastic simulation framework for multivariate processes exhibiting any distribution and any correlation structure. Within case studies we demonstrate two characteristic configurations, i.e., a three-level one, operating at daily, monthly and annual basis, and a two-level one to disaggregate daily to hourly data. The first configuration is applied to generate correlated daily rainfall and runoff data at the river basin of Achelous, Western Greece, which preserves the stochastic behavior of the two processes at the three temporal levels. The second configuration disaggregates daily rainfall, obtained from a meteorological station at Germany, to hourly. The two studies reveal the ability of the proposed framework to represent the peculiar behavior of hydrometeorological processes at multiple temporal resolutions, as well as its flexibility on formulating generic simulation schemes. [ABSTRACT FROM AUTHOR]

Economically optimal management of a continuous cover forest is considered here. Initially, there is a large number of trees of different sizes and the forest may contain several species. We want to optimize the harvest decisions over time, using continuous cover forestry, which is denoted by CCF. We maximize our objective function, the expected present value, with consideration of stochastic prices, timber quality variations and dynamically changing spatial competition. The problem is solved using an adaptive control function. The parameters of the control function are optimized via the first order optimum conditions based on a multivariate polynomial approximation of the objective function. The second order maximum conditions are investigated and used to determine relevant parameter ranges. The procedure is described and optimal results are derived for a general function multi-species CCF forest. Concrete examples from Germany, with beech, and from Sweden, with Norwegian spruce, are used to illustrate the methodology and typical numerical results. It is important to make market adapted harvest decisions. If the stochastic price variations are not considered when the harvest decisions are taken, the expected present value is reduced by 23%. [ABSTRACT FROM AUTHOR]

Summary: Many power plants in Germany and Europe are approaching the end of their technical lifetime. Moreover, the increasing wind and solar power generation reduces the operation times of thermal power plants, making future investments in new generation capacity uncertain under current market conditions. Consequently, the future development of security of power supply is unclear. In this paper, we assess the impact of stochastic fluctuations in power plant availability, renewable generation, and grid load on the future security of supply in Germany. We model variations in power plant availability by application of a combined Mean‐reversion Jump‐diffusion approach. On the basis of that and using Monte‐Carlo methods, we simulate 300 different time series of availability. These profiles are fed into the fundamental power system model REMix, applied to evaluate the appearance of supply shortfalls in hourly resolution. We assess 6 scenarios for the year 2025, differing in renewable generation and demand profiles, as well as grid infrastructure. Geographical focus of the analysis is Germany, but the electricity exchange with its European neighbours is modelled as well. Our results show that the choice of the power plant availability profile can change the loss of load expectation and loss of load hours by up to 50%. However, the influence of load and renewable generation profiles is found to be significantly higher. Assuming that no new conventional power plants are built and existing plants are decommissioned at the end of their empirical lifetime, we identify supply gaps of up to 2.7 GW in Germany. [ABSTRACT FROM AUTHOR]

The popular logit model is extended to allow for varying stochastic parameters (mixed logit) and non-linearities of regressor variables while analysing a cross-sectional sample of German corporate credit defaults. With respect to economic interpretability and goodness of probability forecasts according to disriminatory power and calibration, empirical results favor the extended specifications. The mixed logit model is particularly useful with respect to interpretability. However, probability forecasts based on the mixed logit model are not distinctively preferred to extended logit models allowing for non-linearities in variables. Further potential improvements with the help of the mixed logit approach for panel data are shown in a Monte Carlo study. [ABSTRACT FROM AUTHOR]

. A stochastic epidemic model is defined in which each individual belongs to a household, a secondary grouping (typically school or workplace) and also the community as a whole. Moreover, infectious contacts take place in these three settings according to potentially different rates. For this model, we consider how different kinds of data can be used to estimate the infection rate parameters with a view to understanding what can and cannot be inferred. Among other things we find that temporal data can be of considerable inferential benefit compared with final size data, that the degree of heterogeneity in the data can have a considerable effect on inference for non-household transmission, and that inferences can be materially different from those obtained from a model with only two levels of mixing. We illustrate our findings by analysing a highly detailed dataset concerning a measles outbreak in Hagelloch, Germany. [ABSTRACT FROM AUTHOR]

Abstract: Hybrid systems are often used to describe many complex dynamic phenomena by combining multiple modes of dynamics into whole systems. In this paper, we present a flat Dirichlet process switching (FDPS) model that defines a prior on mode switching dynamics of hybrid systems. Compared with the classical Markovian jump system (MJS) models, the FDPS model is nonparametric and can be applied to the hybrid systems with an unbounded number of potential modes. On the other hand, the probability structure of the new model is simpler and more flexible than the recently proposed hierarchical Dirichlet process (HDP) based MJS. Furthermore, we develop a Markov chain Monte Carlo (MCMC) method for estimating the states of hybrid systems with FDPS prior. And the numerical simulations of a hybrid system in different conditions are employed to show the effectiveness of the proposed approach. [Copyright &y& Elsevier]

This paper investigates both the no-arbitrage condition and the efficiency of financial markets by comparing two stock markets: NYSE and XETRA. We analyze German stocks that are traded simultaneously at both exchanges using high frequency data for XETRA, NYSE, and the foreign exchange rates. Converting Euro-prices into Dollar-prices and vice versa reveals possibilities to explore the efficiency as well as arbitrage opportunities of these two stock markets. One measure of efficiency is the phenomenon of stock price clustering, describing the tendency of prices to cluster at certain prices and avoiding others. We see the result of differing extents of clustering on both exchanges, thus violating the no-arbitrage condition. We propose a trading strategy that exploits these differences. Furthermore, we compare our empirical findings with the results we obtain from simulating financial markets. We conclude that simulations that are based on the no-arbitrage condition are not consistent with our empirical observations. [ABSTRACT FROM AUTHOR]

The stochastic distance function model is extended to allow for the inefficiency component of the error term to be autocorrelated, as implied by a dynamic model of firm behavior. The autocorrelation parameter can then be interpreted as a measure of the persistence of inefficiency. The model is viewed from a state-space perspective, and Kalman filtering techniques are proposed for estimation. The model is applied to two panels of dairy farms from Germany and the Netherlands. The results suggest a very high degree of persistence of inefficiency through time. [ABSTRACT FROM AUTHOR]

Copyright of Schmollers Jahrbuch is the property of Duncker & Humblot GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to tight public budget constraints, the efficiency of publicly financed universities in Germany is receiving increasing attention in the academic as well as in the public discourse. Against this background, we analyse the efficiency of 72 public German universities for the years 1998-2003, applying data envelopment and stochastic frontier analysis. Contrary to earlier studies, we account for the faculty composition of universities which proves to be an essential element in the efficiency of higher education. Our main finding is that East German universities have performed better in total factor productivity change compared to those in West Germany. However, when looking at mean efficiency scores over the sample period, West German universities still appear at the top end of relative efficiency outcomes. [ABSTRACT FROM AUTHOR]

Simulating the random changes of power prices is a crucial task for operational and trading decisions. Currently, models stemming from econometrics and financial mathematics represent the dominating approach to the stochastic simulation of electricity prices. This work proposes a novel methodology based on frequency-domain techniques for simulating the random fluctuations of hourly electricity prices according to probabilistic and spectral properties observed in historical data. The developed nonparametric algorithm is based on the well-known spectral representation method. The method has been extended to accurately reproduce the remarkable non-Gaussian and local nonstationary features of power prices. An iterative procedure and a nonlinear memoryless transformation have been applied to simultaneously match the observed evolutionary spectral content and the marginal non-Gaussian probability density function (PDF) of the random power price fluctuations. The proposed method is general and can be applied to any power market as it does not require the postulation of a model structure and the calibration of model parameters. The method is computationally very efficient as it takes advantage of fast Fourier transform techniques. Spot prices quoted on the German EEX have been selected for extensively testing the quality of the synthetically generated prices. Results show that price samples simulated with the proposed model replicate very accurately both the distributional and time-varying spectral features of the stochastic electricity price dynamics. [ABSTRACT FROM AUTHOR]

The shipyard ''Meyer Werft'' at Papenburg (Germany) is building large cruise liners for customers from all over the world. However, Papenburg is connected to the North Sea only by the small river Ems. Consequently, the navigation of the first 36 km of each large ship poses a serious problem. The position and orientation of the ship must be computed accurately at any time. The track of the ship must also be predicted over the next several minutes in order to derive commands to the pilot. We propose a prediction method based on filtering the observations when the ship rolls due to wind and manoeuvring forces. [ABSTRACT FROM AUTHOR]

Since before the inception of work by Okabe, the intermingling of spatial autocorrelation (i.e., local distance and configuration) and distance decay (i.e., global distance) effects has been suspected in spatial interaction data. This convolution was first treated conceptually because technology and methodology did not exist at the time to easily or fully address spatial autocorrelation effects within spatial interaction model specifications. Today, however, sufficient computer power coupled with eigenfunction-based spatial filtering offers a means for accommodating spatial autocorrelation effects within a spatial interaction model for modest-sized problems. In keeping with Okabe’s more recent efforts to dissemination spatial analysis tools, this paper summarizes how to implement the methodology utilized to analyze a particular empirical flows dataset. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the vibrations in a new tram model (the "Combino Plus") developed by Siemens Company, Germany, which was recently launched on a main Budapest road, and in an older tram model withdrawn from the same line. Comparative measurements were made from terminal to terminal (18 sections). The results of this investigation gave us information about the advances made in relation to the vibrational characteristics of trams. This paper summarizes literature concerning the physiological effects of continuous vibration exposures, as well as the standard ISO 2631, to clarify the relevance of the topic and to draw attention to the recorded parameters of the new "Combino Plus" tram. The new "Combino Plus" tram successfully absorbs the vibrations originating from the roughness of the tram rail. This tram produces significantly less vibration for passengers and drivers than the older model tram withdrawn from the main road traffic. The new Combino Plus satisfies the ergonomic requirements and ensures favorable working conditions. [ABSTRACT FROM AUTHOR]

This work is motivated by a mobility study conducted in the city of Munich, Germany. The variable of interest is a binary response, which indicates whether public transport has been utilized or not. One of the central questions is to identify areas of low/high utilization of public transport after adjusting for explanatory factors such as trip, individual and household attributes. For the spatial effects a modification of a class of Markov random fields (MRF) models with proper joint distributions introduced by Pettitt et al. (2002) is developed. It contains the intrinsic MRF in the limit and allows for efficient Markov Chain Monte Carlo (MCMC) algorithms. Further cluster effects using group and individual approaches are taken into consideration. The first one models heterogeneity between clusters, while the second one models heterogeneity within clusters. A naive approach to include individual cluster effects results in an unidentifiable model. It is shown how a re-parametrization gives identifiable parameters. This provides a new approach for modeling heterogeneity within clusters. Finally, the proposed model classes are applied to the mobility study. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of Spartan spatial random fields (SSRFs) in real-time mapping applications. The data set that we study focuses on the distribution of daily gamma dose rates over part of Germany. Our goal is to determine a Spartan spatial model from the data, and then use it to generate “predictive” maps of the radioactivity. In the SSRF framework, the spatial dependence is determined from sample functions that focus on short-range correlations. A recently formulated SSRF predictor is used to derive isolevel contour maps of the dose rates. The SSRF predictor is explicit. Moreover, the adjustments that it requires by the user are reduced compared to classical geostatistical methods. These features present clear advantages for an automatic mapping system. The performance of the SSRF predictor is evaluated by means of various cross-validation measures. The values of the performance measures are similar to those obtained by classical geostatistical methods. Application of the SSRF method to data that simulate a radioactivity release scenario is also discussed. Hot spots are detected and removed using a heuristic method. The extreme values that appear in the path of the simulated plume are not captured by the currently used Spartan spatial model. Modeling of the processes leading to extreme values can enhance the predictive capabilities of the spatial model, by incorporating physical information. [ABSTRACT FROM AUTHOR]

Copyright of Sozialer Fortschritt is the property of Duncker & Humblot GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

including non-traffic influences in the calculation. These influences are represented by additional load. The combination of responses to load is based on a synthesis of experimental methods (e.g. strain-gauge measurement, temperature measurement, and fatigue tests) and theoretical methods (computer calculation, computer modelling, and statistical evaluation of hydro-meteorological databases). The assessment of the lifetime presented in this article takes into account two important loads - irregular temperature load and dead weight. The comprehensive probabilistic evaluation is described on the real bridge structure (steel railway bridge over the Labe River -Czech Republic). The Monte Carlo method is applied. [ABSTRACT FROM AUTHOR]

Aim Spatial floristic and faunistic data bases promote the investigation of biogeographical gradients in relation to environmental determinants on regional to continental scales. Our aim was to extract major gradients in the distribution of vascular plant species from a grid-based inventory (the German FLORKART data base) and relate them to long-term precipitation and temperature records as well as soil conditions. We present an ordination technique capable of coping with this complex data array. The goal was also to sort out the influence of spatial autocorrelation, assuming floristic autocorrelation is anisotropic. Location Germany, at a spatial resolution of 6′ × 10′. Methods Isometric feature mapping (Isomap) was applied as a nonlinear ordination method. Isomap was coupled to ‘eigenvector-based filters’ for generating spatial reference models representing spatial autocorrelation. What is novel here is that the derived filters are not based on the assumption of equidirectional autocorrelation. Instead, the so-called ‘principal coordinates of anisotropic neighbour matrices’ build filters to test the influence of geographical vicinity in directions of high similarity among observations. Results The Isomap ordination of floristic data explained more than 95% of the data variance in six dimensions. The leading two dimensions (representing about 80% of the FLORKART data variance) revealed clear spatial gradients that could be related to independent effects of temperature, precipitation and soil observations. By contrast, the third and higher FLORKART dimensions were dominated by an antagonism of anisotropic spatial autocorrelation and soil conditions. A subsequent cluster analysis of the floristic Isomap coordinates educed the spatial organization of the floristic survey, indicating a considerable sampling bias. Conclusions We showed that Isomap provides a consistent methodical framework for both ordination and derived spatial filters. The technique is useful for tracing the often nonlinear features of species occurrence data to environmental drivers, taking into account anisotropic spatial autocorrelation. We also showed that sampling biases are a conspicuous source of variance in a frequently used floristic data base. [ABSTRACT FROM AUTHOR]

Human life expectancy has risen in most developed countries over the last century, causing the observed demographic shifts. Babel, Bomsdorf and Schmidt (forthcoming) introduce a stochastic mortality model using panel data procedures which distinguishes between a common time effect and a common age effect of mortality evolvement. Using this mortality model, the present paper provides forecasts of future life expectancy for 17 countries divided into 12 regions: Australia, Alps, Bene, Canada, England and Wales, France, Germany, Italy, Japan, Spain, Scandinavia and the United States of America. We consider (traditional) period life expectancies as well as cohort life expectancies, the latter being a more realistic approach but less common. It turns out that a continuing increase of life expectancy is expected in all considered countries. Further, we show that the probabilistic uncertainty of forecast life expectancies is different if either period life expectancies or cohort life expectancies are considered and, moreover, the uncertainty increases substantially if the error of parameter estimation is included. [ABSTRACT FROM AUTHOR]

Stochastic modeling was used to predict nitrogen dioxide and fine particles [particles collected with an upper 50% cut point of 2.5 μm aerodynamic diameter (PM2.5)] levels at 1,669 addresses of the participants of two ongoing birth cohort studies conducted in Munich, Germany. Alternatively, the Gaussian multisource dispersion model IMMISnet/em was used to estimate the annual mean values for NO2 and total suspended particles (TSP) for the 40 measurement sites and for all study subjects. The aim of this study was to compare the measured NO2 and PM2.5 levels with the levels predicted by the two modeling approaches (for the 40 measurement sites) and to compare the results of the stochastic and dispersion modeling for all study infants (1,669 sites). NO2 and PM2.5 concentrations obtained by the stochastic models were in the same range as the measured concentrations, whereas the NO2 and TSP levels estimated by dispersion modeling were higher than the measured values. However, the correlation between stochastic- and dispersion-modeled concentrations was strong for both pollutants: At the 40 measurement sites, for NO2, r = 0.83, and for PM, r = 0.79; at the 1,669 cohort sites, for NO2, r = 0.83 and for PM, r = 0.79. Both models yield similar results regarding exposure estimate of the study cohort to traffic-related air pollution, when classified into tertiles; that is, 70% of the study subjects were classified into the same category. In conclusion, despite different assumptions and procedures used for the stochastic and dispersion modeling, both models yield similar results regarding exposure estimation of the study cohort to traffic-related air pollutants. [ABSTRACT FROM AUTHOR]

Due to habitat fragmentation many plant species today occur mainly in small and isolated populations. Modeling studies predict that small populations will be threatened more strongly by stochastic processes than large populations, but there is little empirical evidence to support this prediction for plants. We studied the relationship between size of local populations (number of flowering plants) and survival over ten years for 359 populations of eight short-lived, threatened plants in northern Germany (Lepidium campestre, Thlaspi perfoliatum, Rhinanthus minor, R. serotinus, Melampyrum arvense, M. nemorosum, Gentianella ciliata and G. germanica). Overall, 27% of the populations became extinct during the study period. Probability of survival of a local population increased significantly with its size in all but one species ( R. minor). However, estimated population sizes required for 90% probability of survival over 10 years varied widely among species. Survival probability increased with decreasing distance to the nearest conspecific population in R. serotinus, but not in the other species. The mean annual growth rate of surviving populations differed greatly between species, but was only for G. germanica significantly lower than 1, suggesting that there was no general deterministic decline in the number of plants due to deteriorating habitat conditions. We conclude that the extinction of populations was at least partly due to stochastic processes. This is supported by the fact that in all species a considerable proportion of small populations survived and developed into large populations. [ABSTRACT FROM AUTHOR]

This article is concerned with the statistical modeling of the daily structure of the nominal exchange rates in the U.K., Germany, and Japan, as well as their returns in relation to the U.S. dollar by means of using fractionally integrated techniques. Using a version of the tests of Robinson [1994] that permits us to tests I(d) statistical models, the results show that the three time series are I(1), finding strong evidence against fractional integration and against mean reversion. Similarly for the return series, all them appear to be stationary I(0) with no evidence of fractional integration of any degree in any series. [ABSTRACT FROM AUTHOR]

Ulrich (1981) supposes in the hypothesis of humusdisintegration that the balance between polymerisation and breakdown of organic material may be disturbed in chemically well buffered European forest soils. This new aspect of aluminium toxicity may cause nitrogen exceedance in forest ecosystems and subsequent seasonal nitrate output (Eichhorn and Hütterman, 1999). In a research program the substances in the seepage water are monitored in a small woodland in central Germany. We explore these multivariate data for examining possible influences on the process of humusdisintegration and its temporal evolution. As a result, a regression model for carbon is developed, which includes covariables, i.e., other substances, as well as spatial and temporal terms describing systematic variability. Especially iron and aluminium turn out to be very influential in the model. So far our work is a basic step for monitoring the seepage water data by means of stochastic modelling. [ABSTRACT FROM AUTHOR]

This paper investigates the cyclical behavior of four alternative estimates of the van der Werf-Beckmann-Uebe model under the usual assumptions that the exogenous variables are fixed and that the disturbances are serially uncorrelated. As this model is linear we use a spectral analytical approach based on the theory of linear transformations of stochastic processes. We find that time paths of the endogenous variables implied by the disturbances of the four estimates of the model have different shapes in regard to periodicity and variability. But in all cases these cycles are longer than the generally observed five-year business cycle of the Federal Republic of Germany. [ABSTRACT FROM AUTHOR]

We examine the orthogonality assumption of seasonal and nonseasonal components for official quarterly unemployment figures in Germany and the United Stales. Although nonperiodic correlations do not seem lo reject the orthogonality assumption, a periodic analysis based on correlation functions that vary with the seasons indicates the violation of orthogonality. We find that the unadjusted data can be described by periodic autoregressive models with a unit root. In simulations we replicate the empirical findings for the German data, where we use these simple models to generate artificial samples. Multiplicative seasonal adjustment leads to large periodic correlations. Additive adjustment leads to smaller ones. [ABSTRACT FROM AUTHOR]

Newly emerging pandemics like COVID-19 call for predictive models to implement precisely tuned responses to limit their deep impact on society. Standard epidemic models provide a theoretically well-founded dynamical description of disease incidence. For COVID-19 with infectiousness peaking before and at symptom onset, the SEIR model explains the hidden build-up of exposed individuals which creates challenges for containment strategies. However, spatial heterogeneity raises questions about the adequacy of modeling epidemic outbreaks on the level of a whole country. Here, we show that by applying sequential data assimilation to the stochastic SEIR epidemic model, we can capture the dynamic behavior of outbreaks on a regional level. Regional modeling, with relatively low numbers of infected and demographic noise, accounts for both spatial heterogeneity and stochasticity. Based on adapted models, short-term predictions can be achieved. Thus, with the help of these sequential data assimilation methods, more realistic epidemic models are within reach.

The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections.

We specify a Bayesian, geoadditive Stochastic Frontier Analysis (SFA) model to assess hospital performance along the dimensions of resources and quality of stroke care in German hospitals. With 1,100 annual observations and data from 2006 to 2013 and risk-adjusted patient volume as output, we introduce a production function that captures quality, resource inputs, hospital inefficiency determinants and spatial patterns of inefficiencies. With high relevance for hospital management and health system regulators, we identify performance improvement mechanisms by considering marginal effects for the average hospital. Specialization and certification can substantially reduce mortality. Regional and hospital-level concentration can improve quality and resource efficiency. Finally, our results demonstrate a trade-off between quality improvement and resource reduction and substantial regional variation in efficiency., Competing Interests: The authors have declared that no competing interests exist.

One of the tasks of the livestock disease compensation funds of the federal states in Germany is the financial compensation of livestock holders for livestock losses and costs incurred for disease control measures due to certain diseases. Usually, one half of these services are financed through financial reserves built up with the contributions paid by the owners of the respective animal species. The other half is covered by the federal state itself. But there is hardly any reference to how to calculate aforementioned financial reserves. Basically, following an approach presented recently regarding estimations concerning the compensation fund of the federal state of Saxony-Anhalt, in a stochastic modeling of the required reserves concerning the fund of Lower Saxony the anticipated costs within the spatial restriction zones allocated to outbreaks were incorporated for the first time. The overall costs (including the federal state's stakes), the share of the comnensation fund (required reserves) and the the partial costs for a total of 25 categories and subcategories and subcategories of livestock species making up the latter were estimated. It became evident that overall costs/the share of the fund were particularly determined among the diseases by foot-and-mouth disease and among the cost factors by the costs incurred for the compensation of livestock value within the areas surrounding the outbreaks in which all susceptible animals are killed (culling zone). The 80th, 90 and 95th percentile of the established probability distribution of the overall costs referred to a financial volume of about 312, 409 and 540 million euro, while the respective percentiles of the probability distribution of the required reserves of the compensation fund amounted to 175, 225 and 296 million euro.

This study investigated the relationship between hospital specialization and technical efficiency using different measures of specialization, including two novel approaches based on patient volumes rather than patient proportions. It was motivated by the observation that most studies to date have quantified hospital specialization using information about hospital patients grouped into different categories based on their diagnosis, and in doing so have used proportions-thus indirectly assuming that these categories are dependent on one other. In order to account for the diversification of organizations and the idea that hospitals can be specialized in terms of professional expertise or technical equipment within a given diagnosis category, we developed our two specialization measures based on patient volume in each category. Using a one-step stochastic frontier approach on randomly selected data from the annual reports of 1,239 acute care German hospitals for the years 2000 through 2010, we estimated the relationship of inefficiency to exogenous variables, such as specialization. The results show that specialization as quantified by our novel measures has effects on efficiency that are the opposite of those obtained using earlier measures of specialization. These results underscore the importance of always providing an exact definition of specialization when studying its effects. Additionally, a Monte Carlo simulation based on three scenarios is provided to facilitate the choice of a specialization measure for further analysis.

Presents a calendar of international conferences related to quantitative finance, scheduled from May to August 2002. Workshop on Interest Rate Models in Kaiserslautern, Germany; Bachelier Finance Society 2nd World Congress in Crete, Greece; Conference on Stochastic Processes and Their Applications in Australia.

This is the first study to use stochastic frontier analysis to estimate both the technical and cost efficiency of physician practices. The analysis is based on panel data from 3,126 physician practices for the years 2006 through 2008. We specified the technical and cost frontiers as translog function, using the one-step approach of Battese and Coelli to detect factors that influence the efficiency of general practitioners and specialists. Variables that were not analyzed previously in this context (e.g., the degree of practice specialization) and a range of control variables such as a patients' case-mix were included in the estimation. Our results suggest that it is important to investigate both technical and cost efficiency, as results may depend on the type of efficiency analyzed. For example, the technical efficiency of group practices was significantly higher than that of solo practices, whereas the results for cost efficiency differed. This may be due to indivisibilities in expensive technical equipment, which can lead to different types of health care services being provided by different practice types (i.e., with group practices using more expensive inputs, leading to higher costs per case despite these practices being technically more efficient). Other practice characteristics such as participation in disease management programs show the same impact throughout both cost and technical efficiency: participation in disease management programs led to an increase in both, technical and cost efficiency, and may also have had positive effects on the quality of care. Future studies should take quality-related issues into account.

The introduction of prospective hospital reimbursement based on diagnosis-related groups (DRG) has been a conspicuous attempt to decelerate the steady increase of hospital expenditures in the German health sector. In this work, the effect of the financial reform on hospital efficiency is subjected to empirical testing by means of two complementary testing approaches. On the one hand, we apply a two-stage procedure based on non-parametric efficiency measurement. On the other hand, a stochastic frontier model is employed that allows a one-step estimation of both production frontier parameters and inefficiency effects. To identify efficiency gains as a consequence of changes in the hospital incentive structure, we account for technological progress, spatial dependence and hospital heterogeneity. The results of both approaches do not reveal any increase in overall efficiency after the DRG reform. In contrast, a significant decline in overall hospital efficiency over time is observed.

On 26 November 2000, the first autochthonous case of bovine spongiform encephalopathy (BSE) was detected in Germany. Since then, a total of 413 BSE cases have been confirmed, resulting in the culling and destruction of 17 313 heads of cattle. In view of the possible risks for human and animal health, Germany has adopted EU regulations along with some additional requirements concerning active surveillance and response measures after detecting a BSE-positive animal. In this study, we used a stochastic model to estimate the costs incurred by the ensuing legislative amendments responding to BSE between November 2000 and December 2010. The total costs were estimated to range between 1847 and 2094 million Euros. They peaked in 2001 (about 394 million Euros) and declined since. About 54% of the costs (approximately 1000 million Euros) were incurred by the extension of the feed ban for animal protein to all farmed livestock. Active surveillance accounted for 21% (405 million Euros), the incineration of animal protein for 13% (249 million Euros) and the removal of specified risk material for 11% (225 million Euros). Only 1% of the costs was related to response measures after detecting a BSE-positive animal, including indemnity payments for culled cattle and confiscated carcasses at the slaughterhouse., (© 2013 Blackwell Verlag GmbH.)

In this article, we demonstrate a statistical method for fitting the parameters of a sophisticated network and epidemic model to disease data. The pattern of contacts between hosts is described by a class of dyadic independence exponential-family random graph models (ERGMs), whereas the transmission process that runs over the network is modeled as a stochastic susceptible-exposed-infectious-removed (SEIR) epidemic. We fit these models to very detailed data from the 1861 measles outbreak in Hagelloch, Germany. The network models include parameters for all recorded host covariates including age, sex, household, and classroom membership and household location whereas the SEIR epidemic model has exponentially distributed transmission times with gamma-distributed latent and infective periods. This approach allows us to make meaningful statements about the structure of the population-separate from the transmission process-as well as to provide estimates of various biological quantities of interest, such as the effective reproductive number, R. Using reversible jump Markov chain Monte Carlo, we produce samples from the joint posterior distribution of all the parameters of this model-the network, transmission tree, network parameters, and SEIR parameters-and perform Bayesian model selection to find the best-fitting network model. We compare our results with those of previous analyses and show that the ERGM network model better fits the data than a Bernoulli network model previously used. We also provide a software package, written in R, that performs this type of analysis., (© 2012, The International Biometric Society.)

A novel point process model continuous in space-time is proposed for quantifying the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002-2008. Modeling is based on the conditional intensity function (CIF), which is described by a superposition of additive and multiplicative components. As an epidemiological interesting finding, spread behavior was shown to depend on type in addition to age: basic reproduction numbers were 0.25 (95% CI 0.19-0.34) and 0.11 (95% CI 0.07-0.17) for types B:P1.7-2,4:F1-5 and C:P1.5,2:F3-3, respectively. Altogether, the proposed methodology represents a comprehensive and universal regression framework for the modeling, simulation, and inference of self-exciting spatiotemporal point processes based on the CIF. Usability of the modeling in biometric practice is promoted by an implementation in the R package surveillance., (© 2011, The International Biometric Society.)

The introduction of prospective hospital reimbursement based on diagnosis related groups (DRG) in 2004 has been a conspicuous attempt to increase hospital efficiency in the German health sector. As a consequence of the reform a rise of competition for (low cost) patients could be expected. In this paper the competition between hospitals, quantified as spatial spillover estimates of hospital efficiency, is analyzed for periods before and after the reform. We implement a two-stage efficiency model that allows for spatial interdependence among hospitals. Hospital efficiency is determined by means of non-parametric and parametric econometric frontier models. We diagnose a significant increase of negative spatial spillovers characterizing hospital performance in Germany, and thus, confirm the expected rise of competition.

The German hospital market has been subject over the past two decades to a variety of healthcare reforms. Particularly the introduction of diagnosis-related groups (DRGs) in 2004 aimed to increase efficiency of hospitals. The objective of the paper is to review recent studies comparing the efficiency of German public, private non-profit and private for-profit hospitals. The results of the studies are quite mixed. However, in line with the evidence found in studies from other countries, especially the US, the evidence from Germany suggests that private ownership (i.e., private non-profit and private for-profit) is not necessarily associated with higher efficiency compared to public ownership. This may be a surprising result to many policy makers as private for-profit hospitals are often perceived the most efficient ownership type by the public., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

This paper investigates the cost and profit efficiency of German hospitals and their variation with ownership type. It is motivated by the empirical finding that private (for-profit) hospitals - having been shown to be less cost efficient in the past - on average earn higher profits than public hospitals. We conduct a Stochastic Frontier Analysis on a multifaceted administrative German data set combined with the balance sheets of 541 hospitals of the years 2002-2006. The results show no significant differences in cost efficiency but higher profit efficiency of private than of publicly owned hospitals., (2010 John Wiley & Sons, Ltd.)

We explored the transition of 13 X-linked markers across two separate portions of the house mouse hybrid zone, asking whether such a comparison can distinguish the effects of selection from random factors. A heuristic search in the likelihood landscape revealed more complex likelihood profiles for data sampled in two-dimensional (2D) space relative to data sampled along a linear transect. Randomized resampling of localities analyzed for individual loci showed that deletion of sites away from the zone center can decrease cline width estimates whereas deletion of sites close to the center can significantly increase the width estimates. Deleting localities for all loci resulted in wider clines if the number of samples from the center was limited. The results suggest that, given the great variation in width estimates resulting from inclusion/exclusion of sampling sites, the geographic sampling design is important in hybrid zone studies and that our inferences should take into account measures of uncertainty such as support intervals. The comparison of the two transects indicates cline widths are narrower for loci in the central part of the X chromosome, suggesting selection is stronger in this region and genetic incompatibilities may have at least partly common architecture in the house mouse hybrid zone., (© 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.)

Even though bluetongue virus (BTV) transmission is apparently interrupted during winter, bluetongue outbreaks often reappear in the next season (overwintering). Several mechanisms for BTV overwintering have been proposed, but to date, their relative importance remain unclear. In order to assess the probability of BTV overwintering by persistence in adult vectors, ruminants (through prolonged viraemia) or a combination of both, a quantitative risk assessment model was developed. Furthermore, the model allowed the role played by the residual number of vectors present during winter to be examined, and the effect of a proportion of Culicoides living inside buildings (endophilic behaviour) to be explored. The model was then applied to a real scenario: overwintering in Germany between 2006 and 2007. The results showed that the limited number of vectors active during winter seemed to allow the transmission of BTV during this period, and that while transmission was favoured by the endophilic behaviour of some Culicoides, its effect was limited. Even though transmission was possible, the likelihood of BTV overwintering by the mechanisms studied seemed too low to explain the observed re-emergence of the disease. Therefore, other overwintering mechanisms not considered in the model are likely to have played a significant role in BTV overwintering in Germany between 2006 and 2007.