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Data X:
36.43 38.72 49.66 37.7 34.72 51.52 32.26 51.88 50.13 144.69 159.08 146.64 121.21 116.45 117.19 133.82 136.98 121.07 90.99 91.51 116.48 120.43 125.72 114.31 116.63 157.88 115.46 152.5 147.38 147.38 127.7 129.52 120.51 114.97 116.23 117.8 146.61 148.85 114.77 127.83 153.35 154.94 148.37 152.96 161.02 154.34 144.24 178.7 121.86 150.66 196.75 250.12 228.32 238.36 198.25 324.08 431.54 267.83 331.21 248.52 367.71 320.22 51.87 51.3 69.23 57.51 58.3 55.8 68.21 66.63 49.41 49.34 49.02 50.24 49.81 49.25 49.25 49.81 49.25 49.34 48.54 44.97 52.31 53.5 52.35 65.47 68 66.05 62.11 114.06 97.89 112.57 112.42 118.16 129.41 120.64 326.84 328.86 332.35 296.16 89.47 100.05 93.24 92.74 113.08 113.8 83.81 113.16 81.89 97.53 89.43 88.18 87.7 91.17 113.59 116.72 115.92 118.11 114.45 115.78
Data Y:
2 -1 -3 -3 1 -3 2 2 -2 -3 1 -1 1 2 2 2 -2 3 3 3 2 0 0 1 1 -3 3 1 -2 -2 2 1 2 3 3 2 2 0 0 3 1 0 3 1 3 -1 -2 2 2 2 0 -1 -3 1 0 -1 -1 0 -2 0 -1 -2 -1 -1 2 3 3 3 0 3 0 0 0 0 0 0 0 0 -1 -1 -1 -2 -2 2 2 3 3 1 2 2 1 2 3 1 0 -2 -2 -1 -1 0 3 2 0 1 -2 -2 2 1 1 0 3 3 3 3 2 3 3 3 3 3
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
par8 <- 'heat.colors' par7 <- 'N' par6 <- 'Y' par5 <- '0' par4 <- '0' par3 <- '0' par2 <- '50' par1 <- '50' 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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R Server
Big Analytics Cloud Computing Center
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