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CSV
Data X:
16.3 17.4 18.1 18.0 17.8 17.5 17.4 17.7 18.1 18.5 18.7 18.9 19.5 19.9 20.2 20.2 19.9 19.6 19.4 19.6 19.8 20.1 20.2 20.2 20.8 21.2 21.3 20.9 20.6 20.5 20.8 21.3 21.9 22.3 22.6 22.7 23.7 24.3 24.6 24.5 24.5 24.2 24.4 24.8 25.2 25.6 25.9 25.8 26.7 27.1 27.0 26.6 26.1 25.6 25.6 25.6 25.8 26.0 25.9 25.4 26.0 26.0 25.8 25.1 24.5 23.8 23.7 23.6 23.7 23.9 23.8 23.5 23.9 23.9 23.6 23.0 22.4 21.7 21.2 21.1 21.2 21.6
Data Y:
9.8 10.0 10.2 10.3 10.3 10.4 10.6 11.1 11.3 11.4 11.3 11.5 11.5 11.8 11.8 11.9 11.8 11.9 11.9 12.2 12.2 12.1 12.3 12.4 12.5 12.6 12.7 12.4 12.3 11.9 12.0 12.6 13.2 13.6 14.1 14.7 14.7 15.0 15.3 15.5 15.1 15.0 15.2 15.9 16.2 16.8 17.1 17.6 17.9 17.8 17.6 17.1 16.7 16.1 16.2 15.8 15.7 15.7 15.5 15.4 15.3 15.3 15.0 14.6 14.1 13.8 13.7 13.3 13.3 13.6 13.6 13.9 14.1 13.9 13.4 12.9 12.1 11.9 11.8 12.1 12.4 12.5
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
N
display data points
(Y/N)
Y
N
colors
terrain.colors
rainbow
heat.colors
topo.colors
cm.colors
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par8 <- 'terrain.colors' par7 <- 'Y' par6 <- 'Y' par5 <- '0' par4 <- '0' par3 <- '0' par2 <- '50' par1 <- '50' 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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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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