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Data X:
85 96.1 113.6 116.8 102.7 106.8 124.2 117.8 121.6 117.9 111.4 109.8 92.6 104.9 120.3 109.1 93.1 87.3 106.9 102.1 102.4 113.3 100.6 103.5 93.7 102.6 108.1 105.9 87.1 81.8 103.8 95.8 92.7 101.1 88 92.8 89.7 95.6 95.2 96.9 79.2 73.5 99.7 87.8 91.3 93.9 90 89.8 88.9 104.2 110.8 110.5 87.1 89.2 96.5 95.4 101 107.6 93.8 93.8
Data Y:
94.3 99.4 115.7 116.8 99.8 96 115.9 109.1 117.3 109.8 112.8 110.7 100 113.3 122.4 112.5 104.2 92.5 117.2 109.3 106.1 118.8 105.3 106 102 112.9 116.5 114.8 100.5 85.4 114.6 109.9 100.7 115.5 100.7 99 102.3 108.8 105.9 113.2 95.7 80.9 113.9 98.1 102.8 104.7 95.9 94.6 101.6 103.9 110.3 114.1 96.8 87.4 111.4 97.4 102.9 112.7 97 95.1
Data Z:
160 171.4 192 231.2 250.8 268.4 266.9 268.5 268.2 265.3 253.8 243.4 213.6 221 227.3 221.6 222.1 232.2 229.6 238.9 238.2 223.9 215 211.1 210.6 206.6 207 201.7 204.5 204.5 195.1 205.5 187.5 173.5 172.3 167.5 157.5 151.1 148.5 147.9 145.6 139.8 138.9 141.4 148.7 150.9 147.3 144.5 134 135.1 131.4 128.4 127.6 127.4 124 123.5 128 129.9 127.6 121.8
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gridsize on x-axis
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gridsize on y-axis
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plot contours
Y
Y
N
plot points
Y
Y
N
Name of dataset X
Name of dataset Y
Name of dataset Z
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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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