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Data X:
6.6 6.4 6 5.8 5.5 5.4 5.4 5.6 5.5 5.8 5.8 5.7 5.5 5.3 5.2 5.3 5.3 5 4.8 4.9 5.3 6 6.2 6.4 6.4 6.4 6.2 6.1 6 5.9 6.2 6.2 6.4 6.8 6.9 7 7 6.9 6.7 6.6 6.5 6.4 6.5 6.5 6.6 6.7 6.8 7.2 7.6 7.6 7.3 6.4 6.1 6.3 7.1 7.5 7.4 7.1 6.8 6.9 7.2 7.4 7.3 6.9 6.9 6.8 7.1 7.2 7.1 7 6.9 7 7.4 7.5 7.5 7.4 7.3 7 6.7 6.5 6.5 6.5 6.6 6.8 6.9 6.9 6.8 6.8 6.5 6.1 6 5.9 5.8 5.9 5.9 6.2 6.3 6.2 6 5.8 5.5 5.5 5.7 5.8 5.7
Data Y:
5.6 5.3 5 4.7 4.4 4.2 4.2 4.3 4.3 4.7 4.8 4.7 4.6 4.5 4.5 4.8 4.8 4.6 4.3 4.3 4.6 5.4 5.5 5.5 5.3 5.2 5.2 5.4 5.3 5 4.9 4.9 5.3 6.3 6.7 6.7 6.4 6.1 6 6.2 6.1 6 6 5.9 5.9 6 6.1 6.4 6.7 6.7 6.5 5.9 5.6 5.7 6 6.3 6.3 6.2 6.1 6.3 6.5 6.6 6.5 6.2 6.2 5.9 6.1 6.1 6.1 6.1 6.1 6.3 6.7 6.9 6.9 6.9 6.8 6.4 5.9 5.5 5.6 5.6 5.8 5.9 6.1 6.1 6 6 5.8 5.5 5.5 5.4 5.2 5.2 5.2 5.5 5.7 5.7 5.6 5.4 5.1 5.1 5.3 5.3 5.3
Data Z:
8 7.7 7.4 7.3 7 6.9 7.1 7.3 7.1 7.3 7.2 7 6.7 6.4 6.1 6.1 5.9 5.6 5.5 5.7 6.1 6.8 7.1 7.5 7.8 7.9 7.6 7 6.9 7.1 7.9 8 7.9 7.4 7.2 7.3 7.7 7.8 7.6 7.3 7 6.9 7.2 7.3 7.5 7.5 7.7 8.2 8.8 8.7 8.3 7.1 6.8 7.2 8.5 9.1 8.9 8.2 7.6 7.7 8.1 8.3 8.3 7.9 7.8 8 8.5 8.6 8.5 8.1 7.8 7.9 8.2 8.3 8.2 8.1 8 7.8 7.8 7.7 7.7 7.6 7.6 7.8 8 8 7.9 7.7 7.4 6.9 6.7 6.5 6.4 6.6 6.8 7 6.9 6.7 6.4 6.2 5.9 6 6.3 6.3 6.1
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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