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Data X:
99.1 98.6 100.4 100.7 101.3 100.1 100.4 99.5 101.5 100.2 99.7 98.9 100.6 99.8 99.4 100.5 98.9 99.9 102 99.5 100 100.2 99.3 100.9 100.8 103.1 101.5 101.3 100 101.2 103.8 104.2 103.8 104.4 101.8 102 100.6 99.3 94.3 101.8 100.2 103.4 102.9 100.8 103.5 99.6 104.9 104.7 104.4 104.2 104.7 104.4 107.9 105.9 104.8 105.9 107 108.6 106.8 110 108.9 108.8 109.1 108.7 108.7 109 109.2 109.7 108.1 109.4 110.1 107.8
Data Y:
107.4 103.8 103.5 106.6 111 110.1 109.1 108.3 99.5 115.6 90.6 92.9 102 102.7 97.9 102.6 106.7 101.9 103.4 91.2 94.6 91.7 98.8 104.4 100.3 104.2 105.7 108.7 100.2 104.2 101.4 105.4 105.4 111.5 104 103.6 108.4 107.1 108.2 109.2 102.6 108.1 112.8 108.1 110.4 102.7 108.2 109.3 111.2 113.5 114.3 108.6 121.3 116.1 113.1 113 117.4 121.2 121 122 123.1 120.7 123.5 125.8 124.3 130.5 129.2 124.6 128.9 127.8 128.6 132.7
Data Z:
103.5 103.6 103.6 103.2 103.4 101.9 103.8 102 101 103.7 101.1 99.3 115.4 111.9 109 112.8 104.6 106.1 110.7 109.9 112.3 112.5 111.3 113.8 110.2 112 115.2 113.1 110.8 117.3 117.7 115.5 115.2 112.8 115.8 119.3 119.4 113.2 115.4 115.1 115.3 113.3 110.8 113.8 114.8 111.1 112.9 112 118.5 120.1 119.6 118 120.4 118.2 117.5 118.6 119.2 119.9 118.9 118.3 120.3 120.4 119.4 119.1 119.3 119.4 131.4 118.6 116.4 118.8 118.2 116.5
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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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