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Data X:
11326.32 11284.15 11615.77 11656.07 11431.43 11734.32 11782.35 11642.47 11532.96 11615.93 11659.9 11479.39 11348.55 11417.43 11430.21 11628.06 11386.25 11412.87 11502.51 11715.18 11543.55 11516.92 11532.88 11188.23 11220.96 11510.74 11230.73 11268.92 11433.71 11421.99 10917.51 11059.02 10609.66 11019.69 11388.44 11015.69 10854.17 10825.17 11022.06 11143.13 10365.45 10850.66 10831.07 10482.85 10325.38 9955.5 9447.11 9258.1 8579.19 8566.6 9387.61 9310.99 8577.91 8979.26 8852.22 9265.43 9033.66 8519.21 8691.25 8378.95 8175.77 9065.12 8990.96 9180.69 9325.01 9319.83 9625.28 9139.27 8695.79
Data Y:
18810 18890 18370 18405 18350 18360 18445 17520 17760 17980 17380 17280 17650 17875 18010 17935 17925 18225 18130 18270 18265 17920 17900 17985 17985 18240 18110 17630 17160 17290 17630 17590 17730 19280 19010 19300 19510 19530 19480 19265 19700 20125 19985 20085 19545 19875 20050 21735 20865 21820 20550 20160 20080 20050 19260 19280 19100 18955 18265 17760 18760 19280 18920 18950 18490 18470 18570 18900 18485
Data Z:
125.39 123.44 123.27 120.53 117.59 117.69 116.52 114.12 112.38 111.7 112.35 112.3 112.1 111.62 111.62 117.76 117.42 114.12 113.68 115.74 116.23 115.02 111.5 106.95 106.88 107.18 104.74 104.26 101.3 100.59 98.24 97.61 92.15 89.99 91.87 95.09 97.7 100.46 103.66 104.16 101.82 102.24 97.83 96.22 96.31 94.35 91.39 85.94 84.98 82.83 83.22 79.79 76.51 77.67 74.6 68.91 67.27 69.49 70.31 65.99 65.75 61.8 60.67 60.93 62.74 64.12 63.1 62.64 62.62
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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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