Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
26 20 19 19 20 25 25 22 26 22 17 22 19 24 26 21 13 26 20 22 14 21 7 23 17 25 25 19 20 23 22 22 21 15 20 22 18 20 28 22 18 23 20 25 26 15 17 23 21 13 18 19 22 16 24 18 20 24 14 22 24 18 21 23 17 22 24 21 22 16 21 23 22 24 24 16 16 21 26 15 25 18 23 20 17 25 24 17 19 20 15 27 22 23 16 19 25 19 19 26 21 20 24 22 20 18 18 24 24 22 23 22 20 18 25 18 16 20 19 15 19 19 16 17 28 23 25 20 17 23 16 23 11 18 24 23 21 16 24 23 18 20 9 24 25 20 21 25 22 21 21 22 27 24 24 21 18 16 22 20 18 20
Data Y:
21 15 18 11 8 19 4 20 16 14 10 13 14 8 23 11 9 24 5 15 5 19 6 13 11 17 17 5 9 15 17 17 20 12 7 16 7 14 24 15 15 10 14 18 12 9 9 8 18 10 17 14 16 10 19 10 14 10 4 19 9 12 16 11 18 11 24 17 18 9 19 18 12 23 22 14 14 16 23 7 10 12 12 12 17 21 16 11 14 13 9 19 13 19 13 13 13 14 12 22 11 5 18 19 14 15 12 19 15 17 8 10 12 12 20 12 12 14 6 10 18 18 7 18 9 17 22 11 15 17 15 22 9 13 20 14 14 12 20 20 8 17 9 18 22 10 13 15 18 18 12 12 20 12 16 16 18 16 13 17 13 17
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation