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Cross-national analyses are presented that suggest that changes in the variance of voters' policy preferences—in 12 Western European democracies from 1976 to 1998—are associated with corresponding changes in the variance of policy choices on offer in these party systems. This finding is labeled the Voter Distribution Effects Result. There is also evidence to support a second major finding, the Electoral Laws Result, which states that voter distribution effects, i.e., the effects associated with changes in the variance of voters' policy preferences, are stronger in political systems that feature less proportional electoral rules (e.g., plurality voting systems). These findings have implications for party strategies and for our general understanding of political representation.

Suppression of dengue and malaria through releases of genetically engineered mosquitoes might soon become feasible. Aedes aegypti mosquitoes carrying a conditionally lethal transgene have recently been used to suppress local vector populations in small-scale field releases. Prior to releases of transgenic insects on a wider scale, however, most regulatory authorities will require additional evidence that suppression will be effective in natural heterogeneous habitats. We use a spatially explicit stochastic model of an Ae. aegypti population in Iquitos, Peru, along with an uncertainty analysis of its predictions, to quantitatively assess the outcome of varied operational approaches for releases of transgenic strains with conditional death of females. We show that population elimination might be an unrealistic objective in heterogeneous populations. We demonstrate that substantial suppression can nonetheless be achieved if releases are deployed in a uniform spatial pattern using strains combining multiple lethal elements, illustrating the importance of detailed spatial models for guiding genetic mosquito control strategies.

The Gini coefficient is a measure of statistical dispersion that is commonly used as a measure of inequality of income, wealth or opportunity. Empirical research has shown that the coefficient may have a nonnegligible downward bias when data are grouped. It is unknown under which grouping conditions the downward bias occurs. In this note it is shown that the Gini coefficient strictly decreases if the data are partitioned into equal sized groups.

In this paper a class of multivariate dispersion models generated from the multivariate Gaussian copula is presented. Being a multivariate extension of Jørgensen's (1987a) dispersion models, this class of multivariate models is parametrized by marginal position, dispersion and dependence parameters, producing a large variety of multivariate discrete and continuous models including the multivariate normal as a special case. Properties of the multivariate distributions are investigated, some of which are similar to those of the multivariate normal distribution, which makes these models potentially useful for the analysis of correlated non-normal data in a way analogous to that of multivariate normal data. As an example, we illustrate an application of the models to the regression analysis of longitudinal data, and establish an asymptotic relationship between the likelihood equation and the generalized estimating equation of Liang & Zeger (1986).

The access control methods mainly employ physiological characteristics and the practical relevance to generate sophisticated spoofing attacks led to the development of liveness detection methods to increase the robustness of the identification systems. Among the largely deployed traits such as iris and fingerprint, the face is the commonly used modality in recognition systems due to its non-intrusive nature. The evolving technological progress has made the production of a wide variety of spoofing attacks such as Print attacks, Display attack, Replay, and 3D mask attacks possible and hence led to the development of various anti-spoofing methods. Here, a novel approach for face spoof detection addressing print spoof is presented. The novelty lies in distinct features derived from color scatter and variance measures on HSI color space. In an attempt to explore other features, GLCM-based measures are used. The volumetric scatter measures around the convex hull with the geometric description have yielded compact and effective features than GLCM measures and works well with naturally available acquisition devices. Spoof detection rate is highly significant with the color scatter and volumetric features and works well over inter-database protocols too.

In this paper, we examine the relation between stock returns and analysts' heterogeneous expectations. We find that stock returns are positively associated with divergence of opinion. Our evidence provides no support for Miller's (1977) overvaluation hypothesis, which predicts lower (higher) future returns for high (low) divergence of opinion stocks in the presence of short-selling constraints. Our findings are based on the use of the diversity measure, which is free from the confounding effects of uncertainty in analysts' forecasts and is therefore a more accurate measure of divergence of opinion than dispersion. Our results refute the view that dispersion in analysts' forecasts reflects divergence of opinion. Our evidence is robust to the use of alternative measures of short-selling constraints, time intervals, optimism in analysts' forecasts, and herding in analysts' behavior.

Purpose The purpose of this research is to take into consideration the country effect in online and offline environments and compares price levels and dispersion online v. offline across the two largest Continental European markets, thus adding a new dimension in price comparisons and multichannel pricing strategies. Designmethodologyapproach Based on an empirical analysis of data collected in one product category CDs, our findings for France and Germany show that price levels including shipping costs are always higher online than offline in each country and price dispersion is persistent across markets. Calculating mean prices for the two countries, ANOVA tests reveal significant differences among the two sets of data. Using standard deviation as the measurement for price dispersion, Levene statistics reveal a higher degree of online price dispersion than offline and statistically significant differences between the two sample countries. Findings Even if our approach need to be extended to more product categories and more countries, our article may be interesting for practitioners, policy makers and managers. It clearly shows that the frictionless capitalism and cost transparency hypothesis has proven to be wrong most of the time even if many retailers still believe they must sacrifice the possibility of pricing up when they go on the internet. As demonstrated by our findings, retailers can take advantage of online relative indifference to price to capture some margin premium and enjoy excellent results. Originalityvalue Our results also demonstrate that, even if results show some similarities and common trends, differences among France and Germany still remain important. As a consequence, marketers should continue to approach the European marketplace with full awareness of its diversity.

Characterizing the quality of dispersion of nanocomposites presents a challenging statistical problem for which no direct method has been fully adopted. A high precision, statistically well-grounded measure is required which is suitable for dealing with a single small non-homogeneous particle pattern obtained from the material. Our approach uses the Delaunay network of particles to measure the area disorder AD Del which can be further used to categorize a material sample into well or poorly dispersed. AD Del -analysis is applied to several micrographs of nanoparticle-modified materials and found to classify the type of dispersion reliably. Selected spatial point processes are employed to estimate expected imprecision in observed measurements.

Ranked earnings surprise portfolios formed from First Call files for 1992-97 are used to assess the annual earnings surprise magnitude for an individual firm sufficient to expect a \"significant market reaction.\" We find that, for an individual firm, the maximum probability of a gain from trading on prior knowledge of any surprise magnitude is .622. The lack of probable trading gains is due to the S-shaped surprise/return relation and the large variance of returns for a given magnitude of surprise. In turn, we find that the S-shape is related empirically to the dispersion of analyst forecasts. Thus, factors underlying dispersion differences are related to the importance or \"materiality\" of earnings surprise as measured by stock returns and explain at least part of the S-shaped surprise/return relation.

Unsharp masking-based approaches are widely used in consumer electronics and printing technology for increasing the sharpness of the image. In the classical approaches, such improvements are achieved by adding the high-frequency details to the underlying image without considering any noise present in the image. As a result, such approaches yield visually poor results on noise-deteriorated images. In this paper, we propose an adaptive unsharp masking scheme which can tolerate the noise content, i.e., proposed algorithm will perform sharpening operation on the required regions thereby reducing the visual effects of the noise. Experimentally, it has been found out that the proposed approach yields better visual results than classical unsharp masking approach in the presence of noise.