• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Environment and Ecology Research >Multivariate Statistical Methods in Researching Biocultural Diversity
【24h】

Multivariate Statistical Methods in Researching Biocultural Diversity

机译：研究生物文化多样性的多元统计方法

获取原文
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Nonlinear multivariate statistical methods have proven to be useful tools in research issues dealing with biocultural diversity. Namely, these methods have less restrictions in their use, as compared with compatible linear methods. This research is the example of using some of these methods. The three indices of biocultural diversity by the variables of biological and cultural diversity have been predicted, based on population size (POP), areal size (AREA) and overall biological and cultural richness (RICH). Then, we have determined: clusters in which different countries can be grouped based on biocultural diversity indices (POP, AREA, RICH), the latent dimensions of the biocultural diversity in the space of biocultural diversity indices (POP, AREA, RICH) and finally, the association between the indices of biodiversity and cultural diversity (POP, AREA, RICH). General conclusion is that nonlinear multivariate methods (together with cluster analysis), in spite of their robustness, can provide useful information to the researchers, on the issues they are interested in (in this example, about biocultural diversity). Of course, these methods are more convenient than linear methods only in the context of absence of clear linear relationships between the variables of interest, while the overfitting problem couldn't be avoided in both cases.
机译：非线性多元统计方法已被证明是解决生物文化多样性问题的有用工具。即，与兼容的线性方法相比，这些方法的使用限制较少。这项研究是使用其中一些方法的示例。根据人口规模（POP），面积规模（AREA）和整体生物文化丰富度（RICH），通过生物和文化多样性变量预测了生物文化多样性的三个指数。然后，我们确定：可以根据生物文化多样性指数（POP，AREA，RICH）将不同国家分组的集群，在生物文化多样性指数（POP，AREA，RICH）空间中生物文化多样性的潜在维度，最后，即生物多样性指数和文化多样性指数（POP，AREA，RICH）之间的关联。总体结论是，尽管非线性多元方法（以及聚类分析）具有鲁棒性，但仍可以为研究人员提供有关他们感兴趣的问题（在此示例中，有关生物文化多样性）的有用信息。当然，仅在目标变量之间没有明确的线性关系的情况下，这些方法比线性方法更方便，而在两种情况下都无法避免过度拟合的问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号