...
首页> 外文期刊>Journal of Clinical and Diagnostic Research >Spatial Cluster Models: Model to Predict Disease Casual Association with Physical, Social and Environmental Risk Factors in Public Health Research
【24h】

Spatial Cluster Models: Model to Predict Disease Casual Association with Physical, Social and Environmental Risk Factors in Public Health Research

机译:空间集群模型:模型预测公共卫生研究中的物理,社会和环境风险因素的疾病休闲协会

获取原文
           

摘要

Spatial clustering will help us to identify spatial pattern and also predict geographical factors associated with disease. Spatialcluster models are classifed as Global, Local and Focused clusters. This article aims to discuss various types of spatial clustermodels such as Moran I, Geary C, Tango EET, CUSUM, GAM, K function, Scan statistic and other with suitable examples which willsensitise the medical researchers about this technique.
机译:空间聚类将有助于我们识别空间模式,并预测与疾病相关的地理因素。 Spatial Cluster模型被分类为全局,本地和聚焦的集群。本文旨在讨论各种类型的空间集群,如MORAN I,GEARY C,TANGO EET,CUSUM,GAM,K功能,扫描统计和其他具有合适的例子,其中将医学研究人员讨论了该技术。

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