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A Vector Approach to the Analysis of (Patterns with) Spatial Dependence

机译:向量模式(具有模式相关性)的分析

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摘要

. It is evident that the utility of an image or map will depend on the quantity of the information we can extract from it by the analysis of the spatial relationships of the phenomenon represented. For it, tools that describe aspects such as spatial dependence or autocorrelation in patterns are used. The statistic techniques that measure the spatial dependence are very varied, but all of them provide only scalar information about the variation of spatial properties in the pattern, without analyzing the possible directedness of the dependence mentioned. In this work, we make a vector approach to the analysis of spatial dependence, therefore, given a pattern, besides quantifying its autocorrelation level, we will determinate if statistics evidence of directedness exists, calculating the angle where the direction appears. For this we will use a parametric method when the normality of population can be assumed, and a non-parametric method for uniform distribution.
机译:。显然,图像或地图的实用性取决于我们可以通过分析表示的现象的空间关系从中提取的信息量。为此,使用了描述诸如空间依赖性或模式自相关之类的方面的工具。测量空间依赖性的统计技术千差万别,但是所有这些技术仅提供有关模式中空间特性变化的标量信息,而没有分析提到的依赖性的可能方向性。在这项工作中,我们采用矢量方法来分析空间依赖性,因此,给定一种模式,除了量化其自相关水平外,我们还将确定是否存在指向性的统计证据,并计算方向出现的角度。为此,当可以假设总体为正态时,我们将使用参数方法,而对于均匀分布,将使用非参数方法。

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