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Data X:
174.1 180.4 182.6 207.1 213.7 186.5 179.1 168.3 156.5 144.3 138.9 137.8 136.3 140.3 149.1 149.2 140.4 129 124.7 130.8 130.1 133.2 130.1 126.6 124.8 125.3 126.9 120.1 118.7 117.7 113.4 107.5 107.6 114.3 114.9 111.2 109.9 108.6 109.2 106.4 103.7 103 96.9 104.7 102.2 99 95.8 94.5 102.7 103.2 105.6 103.9 107.2 100.7 92.1 90.3 93.4 98.5 100.8 102.3 104.7 101.1 101.4 99.5 98.4 96.3 100.7 101.2 100.3 97.8 97.4 98.6 99.7 99 98.1 97 98.5 103.8 114.4 124.5 134.2 131.8 125.6 119.9 114.9 115.5 112.5 111.4 115.3 110.8 103.7 111.1 113 111.2 117.6 121.7 127.3 129.8 137.1 141.4 137.4 130.7 117.2 110.8 111.4 108.2 108.8 110.2 109.5 109.5 116 111.2 112.1 114 119.1 114.1 115.1 115.4 110.8 116 119.2 126.5 127.8 131.3 140.3 137.3 143 134.5 139.9 159.3 170.4 175 175.8 180.9 180.3 169.6 172.3 184.8 177.7 184.6 211.4
Data Y:
145.9 158.5 152.2 153.7 157.9 154.4 150.7 151.2 147.3 146.6 145.2 139.3 145.7 163.3 181.8 188.1 222.9 206.3 184.9 183.6 186.6 176.5 173.9 184.9 182.5 183.6 172.4 168.9 163.3 152.4 145.8 148.6 143.4 141.2 144.6 144.5 140.8 133.3 127.3 119.6 120.2 121.9 112.4 111 107.8 110.5 118.3 123 112.1 104.2 102.4 100.3 102.6 101.5 103.4 99.4 97.9 98 90.2 87.1 91.8 94.8 91.8 89.3 91.7 86.2 82.8 82.3 79.8 79.4 85.3 87.5 88.3 88.6 94.9 94.7 92.6 91.8 96.4 96.4 107.1 111.9 107.8 109.2 115.3 119.2 107.8 106.8 104.2 94.8 97.5 98.3 100.6 94.9 93.6 98 104.3 103.9 105.3 102.6 103.3 107.9 107.8 109.8 110.6 110.8 119.3 128.1 127.6 137.9 151.4 143.6 143.4 141.9 135.2 133.1 129.6 134.1 136.8 143.5 162.5 163.1 157.2 158.8 155.4 148.5 154.2 153.3 149.4 147.9 156 163 159.1 159.5 157.3 156.4 156.6 162.4 166.8 162.6 168.1
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
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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