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Data X:
90.7 94.3 104.6 111.1 110.8 107.2 99.0 99.0 91.0 96.2 96.9 96.2 100.1 99.0 115.4 106.9 107.1 99.3 99.2 108.3 105.6 99.5 107.4 93.1 88.1 110.7 113.1 99.6 93.6 98.6 99.6 114.3 107.8 101.2 112.5 100.5 93.9 116.2 112.0 106.4 95.7 96.0 95.8 103.0 102.2 98.4 111.4 86.6 91.3 107.9 101.8 104.4 93.4 100.1 98.5 112.9 101.4 107.1 110.8 90.3 95.5 111.4 113.0 107.5 95.9 106.3 105.2 117.2 106.9 108.2 113.0 97.2 99.9 108.1 118.1 109.1 93.3 112.1 111.8 112.5 116.3 110.3 117.1 103.4 96.2
Data Y:
97.8 107.4 117.5 105.6 97.4 99.5 98.0 104.3 100.6 101.1 103.9 96.9 95.5 108.4 117.0 103.8 100.8 110.6 104.0 112.6 107.3 98.9 109.8 104.9 102.2 123.9 124.9 112.7 121.9 100.6 104.3 120.4 107.5 102.9 125.6 107.5 108.8 128.4 121.1 119.5 128.7 108.7 105.5 119.8 111.3 110.6 120.1 97.5 107.7 127.3 117.2 119.8 116.2 111.0 112.4 130.6 109.1 118.8 123.9 101.6 112.8 128.0 129.6 125.8 119.5 115.7 113.6 129.7 112.0 116.8 127.0 112.1 114.2 121.1 131.6 125.0 120.4 117.7 117.5 120.6 127.5 112.3 124.5 115.2 105.4
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
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') 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 bitmap(file='bidensity.png') op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4) image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab) if (par6=='Y') contour(op$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')
Compute
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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