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Data X:
62.2 88.5 93.3 89.2 101.3 97 102.2 100.3 78.2 105.9 119.9 108 77 93.1 109.5 100.4 99 113.9 102.1 101.6 84 110.7 111.6 110.7 73.1 87.5 109.6 99.3 92.1 109.3 94.5 91.4 82.9 103.3 96 104.8 65.8 78.7 100.3 85 94.5 97.9 91.9 87.2 84.4 99.2 105.4 110.9 69.8 86.8 106.7 88.8 96.9 108.1 93.7 94.8 79.8 95.6 107.9 104.9 61.9 85.7 92.4 86.4 99.3 95.5 97 102.1 77.8 105.5 113.2 108.8 66.9 89.3 93.6 92 99.5 98.6 94.6 96.7 75.3 102.5 115.1 104.7 71.4
Data Y:
43.5 37.7 36.8 24.4 31.3 43.9 53.6 48.9 30.9 31.8 41.3 43.7 54.1 47.8 36.7 30.8 31.9 61.7 73 64.7 24.2 33.9 32.4 63.2 71.8 60.4 48 44.5 44.9 70.9 72.7 59.5 35.9 40 43.6 57.2 75.8 57.7 47.7 42.3 43 68 70.6 54.2 38.6 40.3 49.2 68.5 75.9 63.2 49.8 37 48.8 74.9 75.3 66.9 44.1 39.8 56.6 77.1 78.5 70.6 54.2 47.2 55.1 74.5 88 80.8 54.4 55.2 73.8 85.3 98.7 86.1 62.5 58.6 67 88.4 96.5 87.1 61.2 62.5 85.2 101.7 113.7
Data Z:
200.7 146.5 143.6 141.5 137.5 138.7 135.5 136.4 112.1 109 123.8 151.2 139.2 115.7 147.6 126.1 122.8 137.3 142 137.4 89.4 108 117.7 127.3 121 104.1 119.5 116.7 96.1 125 118.8 114.9 79.3 90.5 87.8 109.4 88.9 97.4 112 86.8 82.9 105.2 89.1 85.5 87.1 85.2 88.2 104 96.4 82.3 114.1 88.9 93.6 101.8 96.6 93.7 68.4 68.7 81.2 85.1 75.4 71.6 83 72.3 90.2 89 84.9 90.9 46.6 55.4 88.7 76 76.9 72.1 90 92.3 78 93.9 84.5 80.4 60.5 75.3 91.5 105.2 92.7
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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
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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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