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Data X:
3134.5 3510.5 4047.4 3580.8 3567.3 3920.1 3764.8 3139.3 4126.1 3920 3868.3 3414 3423.4 3819 4482.7 4040.4 3720.3 4405 3916.6 3540.5 4486.4 4213.6 4521.7 4102.3 3854.1 4106.5 4870.9 4559.7 4072.1 4687.7 4096.1 4107.2 4888 4256.2 4593.8 3888.2 4232.7 4386.2 5203.6 4456.6 4828.4 5244.6 4407.6 4809.3 5226.8 5290.2 5068.8 4425.2 4971 4806.9 5565.8 4754.9 5220 5684.3 4815.3 5114.4 5273.9 5602.6 5609.7 4168.9
Data Y:
2236 2084.9 2409.5 2199.3 2203.5 2254.1 1975.8 1742.2 2520.6 2438.1 2126.3 2267.5 2201.1 2128.5 2596 2458.2 2210.5 2621.2 2231.4 2103.6 2685.8 2539.3 2462.4 2693.3 2307.7 2385.9 2737.6 2653.9 2545.4 2848.8 2359.5 2488.3 2861.1 2717.9 2844 2749 2652.9 2660.2 3187.1 2774.1 3158.2 3244.6 2665.5 2820.8 2983.4 3077.4 3024.8 2731.8 3046.2 2834.8 3292.8 2946.1 3196.9 3284.2 3003 2979 3137.4 3647.7 3283 2947.3
Data Z:
3258.1 3140.1 3627.4 3279.4 3204 3515.6 3146.6 2271.7 3627.9 3553.4 3018.3 3355.4 3242 3311.1 4125.2 3423 3120.3 3863 3240.8 2837.4 3945 3684.1 3659.6 3769.6 3592.7 3754 4507.8 3853.2 3817.2 3958.4 3428.9 3125.7 3977 3983.3 4299.6 4306.9 4259.5 3986 4755.6 3925.6 4206.5 4323.4 3816.1 3410.7 4227.4 4296.9 4351.7 3800 4277 4100.2 4672.5 4189.9 4231.9 4654.9 4298.5 3635.9 4505.1 4910.1 4908.7 4101.4
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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Big Analytics Cloud Computing Center
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