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Data X:
100.00 100.00 93.55 88.17 89.25 91.40 92.47 91.40 88.17 87.10 84.95 92.47 93.55 93.55 91.40 90.32 91.40 93.55 93.55 92.47 91.40 89.25 86.02 88.17 87.10 87.10 86.02 84.95 84.95 86.02 86.02 84.95 86.02 82.80 77.42 80.65 78.49 75.27 75.27 75.27 77.42 78.49 76.34 73.12 68.82 65.59 69.89 82.80 84.95 80.65 74.19 70.97 74.19 82.80 86.02 86.02 82.80 78.49 79.57 87.10 89.25
Data Y:
100.00 110.08 123.28 106.30 114.60 110.22 117.82 138.84 131.13 153.26 148.76 110.75 132.00 138.55 126.50 119.47 152.49 152.46 134.08 162.33 130.46 142.83 148.39 122.88 125.86 133.31 140.97 110.30 123.04 125.99 112.24 136.10 111.86 109.63 135.75 114.39 121.79 101.33 147.01 113.01 101.89 117.85 128.68 117.27 121.55 109.18 127.88 104.92 100.93 116.79 107.50 109.18 128.31 83.80 93.16 103.99 106.33 97.55 111.71 105.43 103.62
Data Z:
100.00 100.00 103.56 103.77 98.54 93.10 91.63 90.38 89.33 87.24 85.15 84.10 82.64 81.59 81.59 81.17 81.38 81.38 82.22 82.43 83.05 83.68 84.52 87.45 90.38 91.42 92.05 91.63 91.21 91.21 92.05 92.26 92.68 92.47 93.31 96.44 100.00 102.09 103.56 103.56 103.14 103.14 102.72 102.09 101.05 101.05 101.46 104.39 107.53 110.04 111.51 110.46 104.39 99.37 96.86 94.56 94.14 93.72 93.93 95.61 97.07
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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Big Analytics Cloud Computing Center
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