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Data X:
95.90 96.06 96.31 96.34 96.49 96.22 96.53 96.50 96.77 96.66 96.58 96.63 97.06 97.73 98.01 97.76 97.49 97.77 97.96 98.23 98.51 98.19 98.37 98.31 98.60 98.97 99.11 99.64 100.03 99.98 100.32 100.44 100.51 101.00 100.88 100.55 100.83 101.51 102.16 102.39 102.54 102.85 103.47 103.57 103.69 103.50 103.47 103.45 103.48 103.93 103.89 104.40 104.79 104.77 105.13 105.26 104.96 104.75 105.01 105.15 105.20 105.77 105.78 106.26 106.13 106.12 106.57 106.44 106.54
Data Y:
2.90 2.63 2.67 1.81 1.33 0.88 1.28 1.26 1.26 1.29 1.10 1.37 1.21 1.74 1.76 1.48 1.04 1.62 1.49 1.79 1.80 1.58 1.86 1.74 1.59 1.26 1.13 1.92 2.61 2.26 2.41 2.26 2.03 2.86 2.55 2.27 2.26 2.57 3.07 2.76 2.51 2.87 3.14 3.11 3.16 2.47 2.57 2.89 2.63 2.38 1.69 1.96 2.19 1.87 1.60 1.63 1.22 1.21 1.49 1.64 1.66 1.77 1.82 1.78 1.28 1.29 1.37 1.12 1.51
Data Z:
96.92 96.06 96.59 96.67 97.27 96.38 96.47 96.05 96.76 96.51 96.55 95.97 97.00 97.46 97.90 98.42 98.54 99.00 98.94 99.02 100.07 98.72 98.73 98.04 99.08 99.22 99.57 100.44 100.84 100.75 100.49 99.98 99.96 99.76 100.11 99.79 100.29 101.12 102.65 102.71 103.39 102.80 102.07 102.15 101.21 101.27 101.86 101.65 101.94 102.62 102.71 103.39 104.51 104.09 104.29 104.57 105.39 105.15 106.13 105.46 106.47 106.62 106.52 108.04 107.15 107.32 107.76 107.26 107.89
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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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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