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Data X:
9.829 9.125 9.782 9.441 9.162 9.915 10.444 10.209 9.985 9.842 9.429 10.132 9.849 9.172 10.313 9.819 9.955 10.048 10.082 10.541 10.208 10.233 9.439 9.963 10.158 9.225 10.474 9.757 10.490 10.281 10.444 10.640 10.695 10.786 9.832 9.747 10.411 9.511 10.402 9.701 10.540 10.112 10.915 11.183 10.384 10.834 9.886 10.216 10.943 9.867 10.203 10.837 10.573 10.647 11.502 10.656 10.866 10.835 9.945 10.331
Data Y:
1.493 1.401 1.578 1.503 1.502 1.630 1.665 1.593 1.609 1.526 1.463 1.554 1.524 1.442 1.697 1.515 1.591 1.666 1.592 1.686 1.582 1.617 1.433 1.639 1.570 1.477 1.689 1.583 1.690 1.696 1.680 1.741 1.722 1.638 1.522 1.503 1.676 1.600 1.724 1.535 1.723 1.645 1.713 1.837 1.682 1.673 1.578 1.580 1.759 1.656 1.718 1.759 1.767 1.846 1.864 1.841 1.725 1.799 1.526 1.649
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') 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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Summary of computational transaction
Raw Input
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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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