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Data X:
0.818465 0.800641 0.769764 0.745823 0.762253 0.768403 0.757518 0.772917 0.787774 0.82203 0.830772 0.813537 0.815927 0.832293 0.848464 0.843455 0.826241 0.837661 0.831947 0.81493 0.783085 0.790514 0.788395 0.780579 0.785731 0.792959 0.776337 0.75683 0.76929 0.764877 0.755173 0.739864 0.740138 0.745212 0.729076 0.734107 0.719632 0.702889 0.681013 0.686342 0.67944 0.678058 0.644039 0.63488 0.642797 0.642963 0.634115 0.66778 0.695894 0.750638 0.785423 0.74355 0.755344 0.782167 0.766284 0.75815 0.732601 0.71347 0.709824 0.700869
Data Y:
1076.7 1035.9 1037 1154 1237.2 996.6 1238.2 1153.4 1268.1 1156 1144.5 1232.9 1055.2 1109.7 1079.8 1126.3 1196.8 1130.4 1183.6 1200.9 1426.6 1080.4 1325.4 1230 1125.9 1174.5 1151.9 1439.3 1344.3 1319.1 1257.6 1249.1 1397.1 1348 1548.2 1377.6 1402.9 1167.6 1392.9 1547 1420 1266.4 1280.8 1128.6 1449.5 1511.7 1548.3 1652 1650.5 1370.8 1653.3 1474.3 1418.8 1554.1 1156.6 1223.4 1337.5 1098.9 1037.6 1202.5
Data Z:
1393.2 1108.1 1074.8 1323.5 1367 1190.7 1149.2 1281.9 1406.8 1392.4 1674.5 1529.8 1180.9 1282.8 1524.2 1524.6 1520.1 1881.9 1375.2 1336.5 1653.9 1404.3 1731.4 1330.8 1616.3 1503.7 1476.7 1565.6 1581.8 1407.7 1393.7 1662.4 1929 1352.8 1339.8 1251.2 1491.7 1540.7 1383.7 1827.5 1591.3 1289.2 1292 1368.3 1268.7 1454.4 1252.4 1305.4 1274.9 1089.8 1601.5 1418.9 1208.8 1145.7 1129.1 1073.6 1223.3 1135.5 1091.2 1116.3
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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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1 seconds
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Big Analytics Cloud Computing Center
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