927 resultados para litter mixture
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In this paper we focus on the problem of estimating a bounded density using a finite combination of densities from a given class. We consider the Maximum Likelihood Procedure (MLE) and the greedy procedure described by Li and Barron. Approximation and estimation bounds are given for the above methods. We extend and improve upon the estimation results of Li and Barron, and in particular prove an $O(\\frac{1}{\\sqrt{n}})$ bound on the estimation error which does not depend on the number of densities in the estimated combination.
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Pertenece a un amplio programa infantil de lectura que abarca distintos niveles de edad y, por tanto, de conocimientos. Se abordan las necesidades de lectura en los niños y la amplia variedad de habilidades que necesitan adquirir para su aprendizaje y, se destaca, también, la importancia de la narración en las historias. Chip tiene una horrible aventura en el reino de la basura.
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Se analizan qué son y en qué se concretan las distintas formas de agrupamiento y su influencia en el aprendizaje emocional e instrumental. Estos agrupamientos son: la organización tradicional llamado “mixture”; la separación del alumnado por niveles “streaming” y la “inclusión”. Ésta se caracteriza por el trabajo en grupos heterogéneos y por la presencia en clase de profesionales y voluntarios que apoyan al docente. En este último agrupamiento se obtienen los mejores resultados según la investigación INCLUD-ED sobre educación escolar desarrollada con fondos de la Unión Europea
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Investigation of preferred structures of planetary wave dynamics is addressed using multivariate Gaussian mixture models. The number of components in the mixture is obtained using order statistics of the mixing proportions, hence avoiding previous difficulties related to sample sizes and independence issues. The method is first applied to a few low-order stochastic dynamical systems and data from a general circulation model. The method is next applied to winter daily 500-hPa heights from 1949 to 2003 over the Northern Hemisphere. A spatial clustering algorithm is first applied to the leading two principal components (PCs) and shows significant clustering. The clustering is particularly robust for the first half of the record and less for the second half. The mixture model is then used to identify the clusters. Two highly significant extratropical planetary-scale preferred structures are obtained within the first two to four EOF state space. The first pattern shows a Pacific-North American (PNA) pattern and a negative North Atlantic Oscillation (NAO), and the second pattern is nearly opposite to the first one. It is also observed that some subspaces show multivariate Gaussianity, compatible with linearity, whereas others show multivariate non-Gaussianity. The same analysis is also applied to two subperiods, before and after 1978, and shows a similar regime behavior, with a slight stronger support for the first subperiod. In addition a significant regime shift is also observed between the two periods as well as a change in the shape of the distribution. The patterns associated with the regime shifts reflect essentially a PNA pattern and an NAO pattern consistent with the observed global warming effect on climate and the observed shift in sea surface temperature around the mid-1970s.
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While the standard models of concentration addition and independent action predict overall toxicity of multicomponent mixtures reasonably, interactions may limit the predictive capability when a few compounds dominate a mixture. This study was conducted to test if statistically significant systematic deviations from concentration addition (i.e. synergism/antagonism, dose ratio- or dose level-dependency) occur when two taxonomically unrelated species, the earthworm Eisenia fetida and the nematode Caenorhabditis elegans were exposed to a full range of mixtures of the similar acting neonicotinoid pesticides imidacloprid and thiacloprid. The effect of the mixtures on C. elegans was described significantly better (p<0.01) by a dose level-dependent deviation from the concentration addition model than by the reference model alone, while the reference model description of the effects on E. fetida could not be significantly improved. These results highlight that deviations from concentration addition are possible even with similar acting compounds, but that the nature of such deviations are species dependent. For improving ecological risk assessment of simple mixtures, this implies that the concentration addition model may need to be used in a probabilistic context, rather than in its traditional deterministic manner. Crown Copyright (C) 2008 Published by Elsevier Inc. All rights reserved.
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A primary objective of agri-environment schemes is the conservation of biodiversity; in addition to increasing the value of farmland for wildlife, these schemes also aim to restore natural ecosystem functioning. The management of scheme options can influence their value for delivering ecosystem services by modifying the composition of floral and faunal communities. This study examines the impact of an agri-environment scheme prescription on ecosystem functioning by testing the hypothesis that vegetation management influences decomposition rates in grassy arable field margins. The effects of two vegetation management practices in arable field margins - cutting and soil disturbance (scarification) - on litter decomposition were compared using a litterbag experimental approach in early April 2006. Bags had either small mesh designed to restrict access to soil macrofauna, or large mesh that would allow macrofauna to enter. Bags were positioned on the soil surface or inserted into the soil in cut and scarified margins, retrieved after 44, 103 and 250 days and the amount of litter mass remaining was calculated. Litter loss from the litterbags with large mesh was greater than from the small mesh bags, providing evidence that soil macrofauna accelerate rates of litter decomposition. In the large mesh bags, the proportion of litter remaining in bags above and belowground in the cut plots was similar, while in the scarified plots, there was significantly more litter left in the aboveground bags than in the belowground bags. This loss of balance between decomposition rates above and belowground in scarified margins may have implications for the development and maintenance of grassy arable field margins by influencing nutrient availability for plant communities. (C) 2008 Elsevier B.V. All rights reserved.
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Beetle assemblages and their response to plant community composition and architectural structure were monitored from 2002 to 2006 within arable field margins. Field margins were sown with either tussock grass and forbs, fine grass and forbs or grass only seed mixtures. After an establishment year, field margins were managed using standard sward cuts, scarification, or graminicide application. For predatory beetles, overall density was greatest where tussock grasses were included within the seed mixtures, while the densities of phytophagous beetles were greatest where forbs were present. Unexpectedly, species rarefaction curves suggested that phytophagous beetle species richness was greatest where field margins were established using a grass only seed mixture. The structure of the beetle assemblages, i.e., the relative abundances of individual species, was largely dependent on seed mixture, although margin management also played an important role. The results suggest that field margins established using seed mixtures containing tussock grasses and forbs would be expected to provide the greatest resources for beetles, at least at local scales. However, the use of a single standardised seed mixture for margin establishment would result in a homogenisation of beetle assemblages at a regional scale. (C) 2008 Elsevier B.V. All rights reserved.
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The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.
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Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.
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We investigate the performance of phylogenetic mixture models in reducing a well-known and pervasive artifact of phylogenetic inference known as the node-density effect, comparing them to partitioned analyses of the same data. The node-density effect refers to the tendency for the amount of evolutionary change in longer branches of phylogenies to be underestimated compared to that in regions of the tree where there are more nodes and thus branches are typically shorter. Mixture models allow more than one model of sequence evolution to describe the sites in an alignment without prior knowledge of the evolutionary processes that characterize the data or how they correspond to different sites. If multiple evolutionary patterns are common in sequence evolution, mixture models may be capable of reducing node-density effects by characterizing the evolutionary processes more accurately. In gene-sequence alignments simulated to have heterogeneous patterns of evolution, we find that mixture models can reduce node-density effects to negligible levels or remove them altogether, performing as well as partitioned analyses based on the known simulated patterns. The mixture models achieve this without knowledge of the patterns that generated the data and even in some cases without specifying the full or true model of sequence evolution known to underlie the data. The latter result is especially important in real applications, as the true model of evolution is seldom known. We find the same patterns of results for two real data sets with evidence of complex patterns of sequence evolution: mixture models substantially reduced node-density effects and returned better likelihoods compared to partitioning models specifically fitted to these data. We suggest that the presence of more than one pattern of evolution in the data is a common source of error in phylogenetic inference and that mixture models can often detect these patterns even without prior knowledge of their presence in the data. Routine use of mixture models alongside other approaches to phylogenetic inference may often reveal hidden or unexpected patterns of sequence evolution and can improve phylogenetic inference.