REVIEW ARTICLE MULTIVARIATE EXPLORATORY DATA ANALYSIS AND GRAPHICS:A TUTORIAL

Exploratory data analysis(EDA)is a toolbox of data manipulation methods for looking at data to seewhat they seem to say,i.e.one tries to let the data speak for themselves.In this way there is hope thatthe data will lead to indications about'models'of relationships not expected a priori.In this respect EDAis a pre-step to confirmatory data analysis which delivers measures of how adequate a model is.In thistutorial the focus is on multivariate exploratory data analysis for quantitative data using linear methodsfor dimension reduction and prediction.Purely graphical multivariate tools such as 3D rotation andscatterplot matrices are discussed after having introduced the univariate and bivariate tools on which theyare based.The main tasks of multivariate exploratory data analysis are identified as'search for structure'by dimension reduction and'model selection'by comparing predictive power.Resampling is used tosupport validity,and variables selection to improve interpretability.     

《干旱区地理》1991—1995年载文的统计与分析

对《干旱区地理》５年的刊载论文的学科分布、栏目分布、出版时滞、篇密度、论文来源分布、引用文献等方面,运用统计与分析对比的方法予以回顾和总结,旨在对发表论文及信息质量作出比较客观的评估,以期进一步提高《干旱区地理》的质量。     

南极磷虾资源丰度及其与海冰和表温的关系

根据2003—2010年南极磷虾48.2区产量数据结合该区域海冰和SST数据,分析了磷虾产量的时空分布,探讨了海冰和SST对南极磷虾资源丰度的影响。结果表明,48.2区的渔汛期为3—7月,主要作业时间为2—8月,产量约占该渔区年产量的99.3%。回归分析表明,磷虾CPUE变动与海冰和SST面积变化关系明显。磷虾CPUE与海冰总面积年间变化呈现显著的负相关(R=0.80),与海冰密集度为90%—100%的海冰面积负相关系数最大(R=0.84);年内变化关系则为一元二次多项式回归模型,CPUE随海冰面积的递增先增大后减小,与海冰密集度为60%—70%的海冰面积相关系数最大(R=0.94)。磷虾CPUE与SST为-2—3℃时的总面积年间变化负相关性不显著(R=0.46),但与SST为1—2℃时的面积呈现显著的负相关(R=0.91);年内变化关系也为一元二次多项式回归模型,CPUE随SST面积的递增先增大后减小,与SST为0—1℃时的面积相关系数最大(R=0.97)。