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Data X:
2 2.1 2.1 2.5 2.2 2.3 2.3 2.2 2.2 1.6 1.8 1.7 1.9 1.8 1.9 1.5 1 0.8 1.1 1.5 1.7 2.3 2.4 3 3 3.2 3.2 3.2 3.5 4 4.3 4.1 4 4.1 4.2 4.5 5.6 6.5 7.6 8.5 8.7 8.3 8.3 8.5 8.7 8.7 8.5 7.9 7 5.8 4.5 3.7 3.1 2.7 2.3 1.8 1.5 1.2 1
Data Y:
1.3 1.2 1.1 1.4 1.2 1.5 1.1 1.3 1.5 1.1 1.4 1.3 1.5 1.6 1.7 1.1 1.6 1.3 1.7 1.6 1.7 1.9 1.8 1.9 1.6 1.5 1.6 1.6 1.7 2 2 1.9 1.7 1.8 1.9 1.7 2 2.1 2.4 2.5 2.5 2.6 2.2 2.5 2.8 2.8 2.9 3 3.1 2.9 2.7 2.2 2.5 2.3 2.6 2.3 2.2 1.8 1.8
Data Z:
2.3 1.9 1.7 2.5 2.1 2.4 1.5 1.9 2.1 2.2 2 2 2.2 2.3 2.3 2 2.2 1.9 2.3 2.2 2.3 2.1 2.4 2.3 1.9 1.6 1.8 1.8 2 2.3 2.2 2.2 2 2 1.9 1.5 1.6 1.5 2 1.5 1.5 1.9 1.1 1.5 2.1 2.3 2.6 2.9 3.2 3.2 3.1 3 3.3 2.7 3.6 3.1 2.7 2.6 2.2
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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