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Data X:
8 9.300000191 7.5 8.899999619 10.19999981 8.300000191 8.800000191 8.800000191 10.69999981 11.69999981 8.5 8.300000191 8.199999809 7.900000095 10.30000019 7.400000095 9.600000381 9.300000191 10.60000038 9.699999809 11.60000038 8.100000381 9.800000191 7.400000095 9.399999619 11.19999981 9.100000381 10.5 11.89999962 8.399999619 5 9.800000191 9.800000191 10.80000019 10.10000038 10.89999962 9.199999809 8.300000191 7.300000191 9.399999619 9.399999619 9.800000191 3.599999905 8.399999619 10.80000019 10.10000038 9 10 11.30000019 11.30000019 12.80000019 10 6.699999809
Data Y:
9.100000381 8.699999809 7.199999809 8.899999619 8.300000191 10.89999962 10 9.100000381 8.699999809 7.599999905 10.80000019 9.5 8.800000191 9.5 8.699999809 11.19999981 9.699999809 9.600000381 9.100000381 9.199999809 8.300000191 8.399999619 9.399999619 9.800000191 10.39999962 9.899999619 9.199999809 10.30000019 8.899999619 9.600000381 10.30000019 10.39999962 9.699999809 9.600000381 10.69999981 10.30000019 10.69999981 9.600000381 10.5 7.699999809 10.19999981 9.899999619 8.399999619 10.39999962 9.199999809 13 8.800000191 9.199999809 7.800000191 8.199999809 7.400000095 10.39999962 8.899999619
Sample Range:
(leave blank to include all observations)
From:
To:
xgridsize
ygridsize
xbandwidth
(zero to use default)
ybandwidth
(zero to use default)
correlation
(zero to use actual correlation)
display contours
(Y/N)
Y
Y
N
display data points
(Y/N)
Y
Y
N
colors
terrain.colors
terrain.colors
rainbow
heat.colors
topo.colors
cm.colors
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') par4 <- as(par4,'numeric') par5 <- as(par5,'numeric') library('GenKern') x <- x[!is.na(y)] y <- y[!is.na(y)] y <- y[!is.na(x)] x <- x[!is.na(x)] if (par3==0) par3 <- dpik(x) if (par4==0) par4 <- dpik(y) if (par5==0) par5 <- cor(x,y) if (par1 > 500) par1 <- 500 if (par2 > 500) par2 <- 500 if (par8 == 'terrain.colors') mycol <- terrain.colors(100) if (par8 == 'rainbow') mycol <- rainbow(100) if (par8 == 'heat.colors') mycol <- heat.colors(100) if (par8 == 'topo.colors') mycol <- topo.colors(100) if (par8 == 'cm.colors') mycol <- cm.colors(100) bitmap(file='bidensity.png') op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4) image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab) if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE) if (par7=='Y') points(x,y) (r<-lm(y ~ x)) abline(r) box() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Bandwidth',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'x axis',header=TRUE) a<-table.element(a,par3) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'y axis',header=TRUE) a<-table.element(a,par4) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'correlation used in KDE',header=TRUE) a<-table.element(a,par5) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'correlation(x,y)',header=TRUE) a<-table.element(a,cor(x,y)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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