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Data X:
78 68 70 96 74 111 77 168 82 89 149 60 96 83 130 145 112 131 80 130 140 154 118 94 119 153 116 97 176 75 134 161 111 114 142 238 78 196 125 82 125 129 84 183 119 180 82 71 118 121 68 112 109
Data Y:
9.100000381 8.699999809 7.199999809 8.899999619 8.300000191 10.89999962 10 9.100000381 8.699999809 7.599999905 10.80000019 9.5 8.800000191 9.5 8.699999809 11.19999981 9.699999809 9.600000381 9.100000381 9.199999809 8.300000191 8.399999619 9.399999619 9.800000191 10.39999962 9.899999619 9.199999809 10.30000019 8.899999619 9.600000381 10.30000019 10.39999962 9.699999809 9.600000381 10.69999981 10.30000019 10.69999981 9.600000381 10.5 7.699999809 10.19999981 9.899999619 8.399999619 10.39999962 9.199999809 13 8.800000191 9.199999809 7.800000191 8.199999809 7.400000095 10.39999962 8.899999619
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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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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