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Application of Change-Point Problem to the Detection of Plant Patches

机译:变点问题在植物斑块检测中的应用

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In ecology, if the considered area or space is large, the spatial distribution of individuals of a given plant species is never homogeneous; plants form different patches. The homogeneity change in space or in time (in particular, the related change-point problem) is an important research subject in mathematical statistics. In the paper, for a given data system along a straight line, two areas are considered, where the data of each area come from different discrete distributions, with unknown parameters. In the paper a method is presented for the estimation of the distribution change-point between both areas and an estimate is given for the distributions separated by the obtained change-point. The solution of this problem will be based on the maximum likelihood method. Furthermore, based on an adaptation of the well-known bootstrap resampling, a method for the estimation of the so-called change-interval is also given. The latter approach is very general, since it not only applies in the case of the maximum-likelihood estimation of the change-point, but it can be also used starting from any other change-point estimation known in the ecological literature. The proposed model is validated against typical ecological situations, providing at the same time a verification of the applied algorithms. Keywords Bootstrap - Change-interval - Change-point - Ecological boundary - Edge detection - Plant patches
机译:在生态学中,如果考虑的面积或空间很大,则给定植物物种的个体的空间分布永远不会均匀。植物形成不同的斑块。空间或时间上的同质性变化(特别是相关的变化点问题)是数学统计中的重要研究课题。在本文中,对于给定的沿直线的数据系统,考虑两个区域,其中每个区域的数据来自具有未知参数的不同离散分布。在本文中,提出了一种估计两个区域之间的分布变化点的方法,并给出了对由获得的变化点分隔的分布的估计。该问题的解决方案将基于最大似然法。此外,基于对公知的自举重采样的适应,还给出了一种用于估计所谓的变化间隔的方法。后一种方法非常通用,因为它不仅适用于变化点的最大似然估计,而且还可以从生态文献中已知的任何其他变化点估计开始使用。该模型针对典型的生态环境进行了验证,同时提供了对所应用算法的验证。引导程序-变化间隔-变化点-生态边界-边缘检测-植物斑块

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