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Data X:
106.48 106.83 107.14 107.94 108.46 108.81 108.92 108.99 109.16 109.22 109.43 109.23 109.93 110.09 110.33 110.11 110.35 110.09 110.44 110.39 110.62 110.43 110.46 110.55 110.94 111.56 111.82 111.73 111.57 111.85 112.06 112.2 112.47 112.15 112.36 112.32 112.67 113.02 113.05 113.5 113.67 113.65 114 114.03 114.08 114.49 114.48 114.25 114.68 115.28 115.9 115.87 116.09 116.29 116.76 116.78 116.65 116.46 116.82 116.91
Data Y:
106.22 106.31 107.38 109.31 110.82 111.22 110.66 110.76 110.69 111.08 110.97 110.24 112.51 111.52 112.13 112.23 112.92 111.89 111.99 111.51 112.33 112.04 112.09 111.41 112.61 113.14 113.65 114.26 114.4 114.93 114.86 114.95 116.17 114.6 114.62 113.82 115.02 115.18 115.59 116.6 117.07 116.96 116.66 116.07 116.04 115.81 116.22 115.85 116.43 117.39 119.17 119.24 120.03 119.34 118.49 118.59 117.5 117.56 118.25 118.01
Data Z:
103.7 103.75 103.85 104.02 104.13 104.17 104.18 104.2 104.5 104.78 104.88 104.89 104.9 104.95 105.24 105.35 105.44 105.46 105.47 105.48 105.75 106.1 106.19 106.23 106.24 106.25 106.35 106.48 106.52 106.55 106.55 106.56 106.89 107.09 107.24 107.28 107.3 107.31 107.47 107.35 107.31 107.32 107.32 107.34 107.53 107.72 107.75 107.79 107.81 107.9 107.8 107.86 107.8 107.74 107.75 107.83 107.8 107.81 107.86 107.83
Sample Range:
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gridsize on x-axis
(?)
gridsize on y-axis
(?)
plot contours
Y
N
plot points
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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