907 resultados para Branching Processes in Varying Environments


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One of the key environmental concerns about shrimp farming is the discharge of waters with high levels of nutrients and suspended solids into adjacent waterways. In this paper we synthesize the results of our multidisciplinary research linking ecological processes in intensive shrimp ponds with their downstream impacts in tidal, mangrove-lined creeks. The incorporation of process measurements and bioindicators, in addition to water quality measurements, improved our understanding of the effect of shrimp farm discharges on the ecological health of the receiving water bodies. Changes in water quality parameters were an oversimplification of the ecological effects of water discharges, and use of key measures including primary production rates, phytoplankton responses to nutrients, community shifts in zooplankton and delta(15)N ratios in marine plants have the potential to provide more integrated and robust measures. Ultimately, reduction in nutrient discharges is most likely to ensure the future sustainability of the industry. (C) 2003 Elsevier Ltd. All rights reserved.

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Multitype branching processes (MTBP) model branching structures, where the nodes of the resulting tree are particles of different types. Usually such a process is not observable in the sense of the whole tree, but only as the “generation” at a given moment in time, which consists of the number of particles of every type. This requires an EM-type algorithm to obtain a maximum likelihood (ML) estimate of the parameters of the branching process. Using a version of the inside-outside algorithm for stochastic context-free grammars (SCFG), such an estimate could be obtained for the offspring distribution of the process.

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2000 Mathematics Subject Classification: 60J80, 60J85, 62P10, 92D25.

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2000 Mathematics Subject Classification: 60J80

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2000 Mathematics Subject Classification: 60J80.

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2000 Mathematics Subject Classification: 60J80.

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2000 Mathematics Subject Classi cation: 60J80.

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We build the Conditional Least Squares Estimator of 0 based on the observation of a single trajectory of {Zk,Ck}k, and give conditions ensuring its strong consistency. The particular case of general linear models according to 0=( 0, 0) and among them, regenerative processes, are studied more particularly. In this frame, we may also prove the consistency of the estimator of 0 although it belongs to an asymptotic negligible part of the model, and the asymptotic law of the estimator may also be calculated.

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2000 Mathematics Subject Classification: 60J80, 62M05

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2000 Mathematics Subject Classification: 60J80, 60G70.

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This study is focused on the comparison and modification of different estimates arising in the branching processes. Simulations of models with or without migration are put through. Due to the complexity of the computations the algorithms are designed with the language of technical computing MATLAB. Using the simulations, estimates of the o spring mean of the generated processes are calculated. It is well known in the literature that under certain conditions the asymptotic distribution of the estimates is proved to be normal. Using the asymptotic normality a modified method of maximum likelihood is proposed. The aim is to obtain trimmed maximum likelihood estimates based on several sample paths with the same number of generations. Thus in a natural way the observations, inconsistent with the aprior information about the asymptotic normality are excluded from the model. The computation of the standard error allows the comparison of different types of estimates.

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2010 Mathematics Subject Classification: Primary 60J80; Secondary 92D30.