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Data X:
2756.76 2849.27 2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.10 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.40 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.40 3857.62 3801.06 3504.37 3032.60 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41 1810.99 1670.07 1864.44 2052.02 2029.60 2070.83 2293.41 2443.27
Data Y:
10001.60 10411.75 10673.38 10539.51 10723.78 10682.06 10283.19 10377.18 10486.64 10545.38 10554.27 10532.54 10324.31 10695.25 10827.81 10872.48 10971.19 11145.65 11234.68 11333.88 10997.97 11036.89 11257.35 11533.59 11963.12 12185.15 12377.62 12512.89 12631.48 12268.53 12754.80 13407.75 13480.21 13673.28 13239.71 13557.69 13901.28 13200.58 13406.97 12538.12 12419.57 12193.88 12656.63 12812.48 12056.67 11322.38 11530.75 11114.08 9181.73 8614.55 8595.56 8396.20 7690.50 7235.47 7992.12 8398.37 8593.01 8679.75 9374.63 9634.97
Data Z:
49.14 44.61 40.22 44.23 45.85 53.38 53.26 51.8 55.3 57.81 63.96 63.77 59.15 56.12 57.42 63.52 61.71 63.01 68.18 72.03 69.75 74.41 74.33 64.24 60.03 59.44 62.5 55.04 58.34 61.92 67.65 67.68 70.3 75.26 71.44 76.36 81.71 92.6 90.6 92.23 94.09 102.79 109.65 124.05 132.69 135.81 116.07 101.42 75.73 55.48 43.8 45.29 44.01 47.48 51.07 57.84 69.04 65.61 72.87 68.41
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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