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Data X:
6 24 14 25 8 9.3 11 4 94 25 5.5 15.5 8 17 5.5 8.5 6.5 14 6.5 4 14.5 19 5 5 13.5 30.5 13 19 7 12.5 25 35.4 14 15.5 15 22 16.5 4 10 10 12 8 6 39 5.5 9.7 8 29 24.2 13 17.5 7.5 52 16 18 16 11 7 27 15.2 11.5 5 12.5
Data Y:
3.709999994 3.634145353 2.199999999 1.928673056 4.854339324 4.334407088 7.793696038 2.695144611 0.767254237 0.054557923 3.08351422 -1.701249763 1.317777804 2.295089687 1.870992639 5.14510637 2.259075894 2.992337502 1.965657375 6.24941822 4.079933305 -5.479037108 0.677098149 -3.559864876 6.577374352 6.402564845 2.033546407 5.517022938 1.686523279 2.311392474 7.3 -2.367061944 -0.471566848 -3.78964989 7.960433349 1.639819649 4.86496856 3.358760114 7.100000092 2.463732399 3.815717917 1.402662177 0.601886135 3.606960459 1.898691753 19.59233153 -0.798465536 4.503725626 5.039493675 0.584478088 5.041716665 1.237755909 0.013786544 5.988926547 2.953816768 6.500000353 3.510608639 8.487372187 4.200000018 1.635449055 1.915161833 2.531920616 7.70230704
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
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R Server
Big Analytics Cloud Computing Center
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