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Data X:
91.02 91.19 91.53 91.88 92.06 92.32 92.67 92.85 92.82 93.46 93.23 93.54 93.29 93.20 93.60 93.81 94.62 95.22 95.38 95.31 95.30 95.57 95.42 95.53 95.33 95.90 96.06 96.31 96.34 96.49 96.22 96.53 96.50 96.77 96.66 96.58 96.63 97.06 97.73 98.01 97.76 97.49 97.77 97.96 98.23 98.51 98.19 98.37 98.31 98.60 98.97 99.11 99.64 100.03 99.98 100.32 100.44 100.51 101.00 100.88 100.55 100.83 101.51 102.16 102.39 102.54 102.85 103.47 103.57 103.69 103.50 103.47 103.45 103.48 103.93 103.89 104.40 104.79 104.77 105.13 105.26 104.96 104.75 105.01 105.15 105.20 105.77 105.78 106.26 106.13 106.12 106.57 106.44 106.54 107.10 108.10 108.40 108.84 109.62 110.42 110.67 111.66 112.28 112.87 112.18 112.36 112.16 111.49 111.25 111.36 111.74 111.10 111.33 111.25 111.04 110.97 111.31 111.02 111.07 111.36
Data Y:
8 9 11 13 12 13 15 13 16 10 14 14 15 13 8 7 3 3 4 4 0 -4 -14 -18 -8 -1 1 2 0 1 0 -1 -3 -3 -3 -4 -8 -9 -13 -18 -11 -9 -10 -13 -11 -5 -15 -6 -6 -3 -1 -3 -4 -6 0 -4 -2 -2 -6 -7 -6 -6 -3 -2 -5 -11 -11 -11 -10 -14 -8 -9 -5 -1 -2 -5 -4 -6 -2 -2 -2 -2 2 1 -8 -1 1 -1 2 2 1 -1 -2 -2 -1 -8 -4 -6 -3 -3 -7 -9 -11 -13 -11 -9 -17 -22 -25 -20 -24 -24 -22 -19 -18 -17 -11 -11 -12 -10
Data Z:
90.73 91.19 91.53 91.88 92.06 92.32 92.67 92.85 92.82 93.46 93.23 93.54 93.29 93.2 93.6 93.81 94.62 95.22 95.38 95.31 95.3 95.57 95.42 95.53 95.33 95.90 96.06 96.31 96.34 96.49 96.22 96.53 96.50 96.77 96.66 96.58 96.63 97.06 97.73 98.01 97.76 97.49 97.77 97.96 98.23 98.51 98.19 98.37 98.31 98.60 98.97 99.11 99.64 100.03 99.98 100.32 100.44 100.51 101.00 100.88 100.55 100.83 101.51 102.16 102.39 102.54 102.85 103.47 103.57 103.69 103.5 103.47 103.45 103.48 103.93 103.89 104.4 104.79 104.77 105.13 105.26 104.96 104.75 105.01 105.15 105.2 105.77 105.78 106.26 106.13 106.12 106.57 106.44 106.54 107.1 108.1 108.4 108.84 109.62 110.42 110.67 111.66 112.28 112.87 112.18 112.36 112.16 111.49 111.25 111.36 111.74 111.1 111.33 111.25 111.04 110.97 111.31 111.02 111.07 111.36
Sample Range:
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gridsize on x-axis
(?)
gridsize on y-axis
(?)
plot contours
Y
Y
N
plot points
Y
Y
N
Name of dataset X
Name of dataset Y
Name of dataset Z
Chart options
R Code
x <- array(x,dim=c(length(x),1)) colnames(x) <- par5 y <- array(y,dim=c(length(y),1)) colnames(y) <- par6 z <- array(z,dim=c(length(z),1)) colnames(z) <- par7 d <- data.frame(cbind(z,y,x)) colnames(d) <- list(par7,par6,par5) par1 <- as.numeric(par1) par2 <- as.numeric(par2) if (par1>500) par1 <- 500 if (par2>500) par2 <- 500 if (par1<10) par1 <- 10 if (par2<10) par2 <- 10 library(GenKern) library(lattice) panel.hist <- function(x, ...) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='black', ...) } bitmap(file='cloud1.png') cloud(z~x*y, screen = list(x=-45, y=45, z=35),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file='cloud2.png') cloud(z~x*y, screen = list(x=35, y=45, z=25),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file='cloud3.png') cloud(z~x*y, screen = list(x=35, y=-25, z=90),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file='pairs.png') pairs(d,diag.panel=panel.hist) dev.off() x <- as.vector(x) y <- as.vector(y) z <- as.vector(z) bitmap(file='bidensity1.png') op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=cor(x,y), xbandwidth=dpik(x), ybandwidth=dpik(y)) image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,y)',xlab=par5,ylab=par6) if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=='Y') points(x,y) (r<-lm(y ~ x)) abline(r) box() dev.off() bitmap(file='bidensity2.png') op <- KernSur(y,z, xgridsize=par1, ygridsize=par2, correlation=cor(y,z), xbandwidth=dpik(y), ybandwidth=dpik(z)) op image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (y,z)',xlab=par6,ylab=par7) if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=='Y') points(y,z) (r<-lm(z ~ y)) abline(r) box() dev.off() bitmap(file='bidensity3.png') op <- KernSur(x,z, xgridsize=par1, ygridsize=par2, correlation=cor(x,z), xbandwidth=dpik(x), ybandwidth=dpik(z)) op image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,z)',xlab=par5,ylab=par7) if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=='Y') points(x,z) (r<-lm(z ~ x)) abline(r) box() dev.off()
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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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