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Data X:
46.4 392 0.4 68.5 45.7 118 0.61 87.8 45.3 44 0.53 115.8 38.6 158 0.53 106.8 37.2 81 0.53 71.6 35 374 0.37 60.2 34 187 0.3 118.7 28.3 993 0.19 33.7 24.7 1723 0.12 27.2 24.7 287 0.2 62 24.4 970 0.19 24.9 22.7 885 0.12 22.9 22.3 200 0.53 65.7 21.7 575 0.14 21.6 21.6 688 0.34 32.4 21.3 48 0.69 108.7 21.2 572 0.49 38.6 20.8 239 0.42 46.7 20.3 244 0.48 56.5 18.9 472 0.25 44.4 18.8 134 0.52 47.4 18.6 633 0.19 21.7 18 295 0.44 55.7 17.6 906 0.24 27.1 17 1045 0.16 28.5 16.7 775 0.1 41.6 15.9 619 0.15 44.6 15.3 901 0.05 26.1 15 910 0.24 18.7 14.8 556 0.22 49.1
Names of X columns:
HIV_Risk Per_Capita_Income Prop_Population_on_Farms Homicides
R Code
library(corpcor) x <- t(y) (r1 <- pcor.shrink(x)) (r0 <- cor(x)) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Correlation Matrix',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('r0'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable0.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Partial Pearson Correlation Matrix (Shrinkage Method)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('r1'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab')
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Big Analytics Cloud Computing Center
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