Carbon Dioxide Emissions. A Multivariate Analysis HJ-Biplot, Clustering Biplot and Clustering Disjoint Biplot

Pilacuan Bonete Luis, Galindo Villardon Purificación
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Abstract

This document studies graphically, through cluster groups, 17 countries in Europe and South America, generating an order with respect to different variables of public spending, education, environmental, public security, this in order to know the relationship they have with the Carbon Dioxide emissions variable, and generate a multivariate appreciation, using a comparison between the HJBiplot methods of the MulBiplot software, Clustering Biplot and Clustering Disjoint Biplot, using the RStudio software. The clusters obtained allow us to interpret in a broader context the relationship and variability of each country in relation to a set of variables, and to know the homogeneity between countries. In conclusion, using the three grouping methods with certain similarities since all three use the HJ-Biplot within their processes, but differ in others, it was possible to observe how the carbon dioxide emissions, considered as one of the gases causing the greenhouse effect maintains a positive relationship with the economic growth of the countries represented by the GDP per capita, since in the three groups by cluster both variables remain always related, while the variable of Expenditure in Research presents a positive relationship also with respect to these variables, however in the CDBiplot is part of a different factorial axis than the other two variables.
二氧化碳排放。多变量分析hj双图、聚类双图和聚类不相交双图
本文通过对欧洲和南美17个国家的聚类组进行图形化研究,就公共支出、教育、环境、公共安全等不同变量生成一个顺序,从而了解它们与二氧化碳排放变量之间的关系,并通过对MulBiplot软件中的HJBiplot方法、聚类双图和聚类Disjoint双图的比较,生成一个多变量的评价。使用RStudio软件。所获得的集群使我们能够在更广泛的背景下解释每个国家相对于一组变量的关系和可变性,并了解国家之间的同质性。总之,使用具有一定相似性的三种分组方法(因为所有三种方法都在其过程中使用HJ-Biplot,但在其他方面有所不同),可以观察到二氧化碳排放(被认为是导致温室效应的气体之一)如何与以人均国内生产总值为代表的国家的经济增长保持正相关关系,因为在聚类的三组中,这两个变量始终保持相关。虽然研究支出的变量也与这些变量呈正相关,但在CDBiplot中,与其他两个变量相比,它是一个不同的因子轴的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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