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Data X:
14.15 13.95 13.96 13.99 14.08 14.03 13.93 13.95 13.94 14.01 13.98 13.84 14.16 13.92 13.97 14 14 13.87 13.94 13.98 13.95 14.01 13.96 13.88 13.76 13.79 13.97 13.84 13.94 13.97 13.92 13.87 13.9 13.85 13.7 13.87 13.74 13.64 13.83 13.88 14.01 13.98 14.02 14.1 14.11 14.14 14.04 14.19 14.17 14.14 13.94 14.09 14.06 14.07 14.07 14.07 14.05 13.99 13.85 13.95 14.13 14.2 14.2 14.18 14.13 14.07 14.06 14.07 14.1 14.1 14 14.16 13.85 13.97 13.91 13.9 13.83 13.9 13.79 13.88 13.94 13.95 14.08 13.87 14.16 13.9 13.74 13.82 13.82 13.88 13.9 14.04 13.92 13.96 13.8 13.74 13.84 13.71 13.78 13.78 13.76 13.81 13.87 13.76 13.82 13.82 13.83 13.91 13.92 14 13.99 14.01 14.09 14.13 14.03 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.03 14.04 13.9 14.09 14.16 14.09 14.08 13.95 14.01 14 13.99 14 14.02 14.06 14.02 13.97 14.19 13.97 13.98 14.03 14.04 14.13 14.22 14.21 14.15 14.17 14.03 14.02 13.91 13.81 13.78 13.83 13.96 13.9 14.1 13.99 13.9 13.88 13.89 14.03 14.19 14.16 14.1 14.03 14.06 14.07 14.11 14.17 14.23 14.11 14.25 14.03 14.07 13.99 14.01 13.98 13.93 14.06 13.98 14 13.86 13.98 13.8 13.8 13.89 13.88 13.78 13.89 13.93 13.95 13.92 13.96 13.91 13.76 13.79 13.99 13.99 13.99 14.04 14.01 14.13 14.01 14.07 14.04 14.18 14.26 14.31 14.26 14.2 14.18 14.14 14.08 14 14.04 14.08 14 13.94 13.83 13.75 13.92 13.91 13.91 13.9 13.95 14.02 13.89 13.89 13.89 13.87 14.03 13.96 14.06 13.98 14.08 13.95 13.95 13.84 13.94 13.88 13.83 13.8 13.92 13.9 13.73 13.87 13.76 13.86 13.9 13.85 13.9 13.75 13.87 13.97 13.97 14.14 14.18 14.17 14.2 14.17 14.15 14.1 14.04 14.01 14.15 14.03 14.04 14.05 14.12 14.09 13.98 13.94 14.04 13.86 14.03 13.99 14.08 14.01 14.04 13.9 14.09 14.04 13.97 14.08 13.99 14.11 14.16 14.18 14.18 14.38 14.18 14.22 14.13 14.2 14.25 14.14 14.15 14.13 14.1 14.09 14.23 14.11 14.4 14.3 14.37 14.24 14.14 14.17 14.19 14.24 14.11 14.07 14.15 14.28 14.03 14.06 13.94 14.05 14.12 14 14.12 13.99 14.04 14.05 14.06 14.33 14.45 14.39 14.39 14.23 14.25 14.15 14.12 14.26 14.28 14.12 14.29 14.12 14.22 14.09 14.17 14.01 14.22 13.98 14.12 14.09 14.11 14.05 13.96 13.81 14.09 13.87 14.1 14.08 14.09 14.08 13.95 14.08 14 14.05 13.98 14.04 14.24 14.28 14.23 14.16 14.11 14.07 14.07 14.08 14.02 14.08 14.01 14.08 14.23 14.39 14.13 14.21 14.21 14.26 14.36 14.18 14.34 14.26 14.22 14.46 14.51 14.32 14.44 14.35 14.3 14.32 14.24 14.27 14.26 14.26 14.05 14.22 14.11 14.25 14.26 14.16 14.07 14.06 14.22 14.24 14.25 14.23 14.14 14.29 14.33 14.34 14.65 14.43 14.32 14.31 14.34 14.28 14.23 14.4 14.45 14.39 14.35 14.43 14.29 14.41 14.31 14.42 14.43 14.3 14.36 14.22 14.16 14.2 14.38 14.37 14.34 14.19 14.22 14.15 14 14.01 13.94 14 13.93 14.13 14.28 14.26 14.3 14.18 14.18 14.1 14.09 14.03 14.02 14.16 14 14.14 14.28 13.94 14.25 14.26 14.22 14.29 14.2 14.19 14.25 14.38 14.37 14.29 14.44 14.7 14.44 14.34 14.11 14.33 14.46 14.37 14.24 14.42 14.37 14.26 14.23 14.43 14.25 14.2 14.21 14.18 14.3 14.32 14.16 14.15 14.28 14.31 14.27 14.31 14.46 14.33 14.31 14.43 14.28 14.36 14.45 14.5 14.55 14.53 14.55 14.83 14.56 14.58 14.59 14.59 14.67 14.6 14.43 14.42 14.4 14.51 14.45 14.64 14.27 14.28 14.23 14.28 14.26 14.27 14.25 14.3 14.32 14.37 14.21 14.49 14.46 14.5 14.3 14.31 14.28 14.37 14.29 14.21 14.21 14.19 14.38 14.4 14.56 14.42 14.47 14.45 14.46 14.45 14.45 14.43 14.68 14.47 14.74 14.75 14.81 14.54 14.51 14.43 14.53 14.43 14.46 14.48 14.51 14.33
Data Y:
2.64971462 2.63547951 2.6361961 2.63834279 2.64475535 2.64119789 2.63404479 2.63547951 2.63476241 2.63977136 2.63762774 2.62756295 2.65042109 2.63332665 2.63691217 2.63905733 2.63905733 2.62972823 2.63476241 2.63762774 2.63547951 2.63977136 2.6361961 2.63044896 2.62176583 2.62394369 2.63691217 2.62756295 2.63476241 2.63691217 2.63332665 2.62972823 2.63188884 2.62828523 2.61739583 2.62972823 2.62031129 2.61300665 2.62684015 2.63044896 2.63977136 2.63762774 2.64048488 2.6461748 2.64688377 2.64900766 2.6419104 2.65253749 2.65112705 2.64900766 2.63476241 2.64546533 2.64333389 2.64404487 2.64404487 2.64404487 2.6426224 2.63834279 2.62828523 2.63547951 2.6483002 2.65324196 2.65324196 2.65183252 2.6483002 2.64404487 2.64333389 2.64404487 2.6461748 2.6461748 2.63905733 2.65042109 2.62828523 2.63691217 2.63260801 2.63188884 2.62684015 2.63188884 2.62394369 2.63044896 2.63476241 2.63547951 2.64475535 2.62972823 2.65042109 2.63188884 2.62031129 2.62611682 2.62611682 2.63044896 2.63188884 2.6419104 2.63332665 2.6361961 2.62466859 2.62031129 2.62756295 2.61812549 2.62321827 2.62321827 2.62176583 2.62539297 2.62972823 2.62176583 2.62611682 2.62611682 2.62684015 2.63260801 2.63332665 2.63905733 2.63834279 2.63977136 2.64546533 2.6483002 2.64119789 2.6461748 2.6426224 2.64048488 2.64688377 2.65394594 2.66583835 2.65535241 2.6461748 2.6419104 2.64759223 2.63905733 2.64688377 2.64119789 2.64119789 2.6419104 2.64333389 2.6461748 2.64688377 2.64759223 2.65605491 2.65112705 2.64475535 2.64404487 2.64546533 2.64048488 2.63977136 2.63762774 2.63332665 2.64119789 2.63977136 2.65253749 2.61958322 2.63332665 2.63476241 2.64119789 2.6419104 2.64119789 2.64404487 2.6419104 2.63404479 2.65112705 2.64333389 2.65324196 2.65042109 2.64688377 2.65042109 2.6483002 2.63977136 2.6426224 2.6419104 2.6461748 2.6426224 2.64048488 2.64688377 2.65394594 2.66583835 2.65535241 2.6461748 2.6419104 2.64759223 2.63905733 2.64688377 2.64119789 2.64119789 2.6419104 2.64333389 2.6461748 2.64688377 2.64759223 2.65605491 2.65112705 2.64475535 2.64404487 2.64546533 2.64048488 2.63977136 2.63762774 2.63332665 2.64119789 2.63977136 2.65253749 2.61958322 2.63332665 2.63476241 2.64119789 2.6419104 2.64119789 2.64404487 2.6419104 2.63404479 2.65112705 2.64333389 2.65324196 2.65042109 2.64688377 2.65042109 2.6483002 2.63977136 2.6426224 2.6419104 2.64119789 2.6419104 2.63188884 2.64546533 2.65042109 2.64546533 2.64475535 2.63547951 2.63977136 2.63905733 2.63834279 2.63905733 2.64048488 2.64333389 2.64048488 2.63691217 2.65253749 2.63691217 2.63762774 2.64119789 2.6419104 2.6483002 2.65464942 2.65394594 2.64971462 2.65112705 2.64119789 2.64048488 2.63260801 2.62539297 2.62321827 2.62684015 2.6361961 2.63188884 2.6461748 2.63834279 2.63188884 2.63044896 2.63116916 2.64119789 2.65253749 2.65042109 2.6461748 2.64119789 2.64333389 2.64404487 2.64688377 2.65112705 2.65535241 2.64688377 2.65675691 2.64119789 2.64404487 2.63834279 2.63977136 2.63762774 2.63404479 2.64333389 2.63762774 2.63905733 2.62900699 2.63762774 2.62466859 2.62466859 2.63116916 2.63044896 2.62321827 2.63116916 2.63404479 2.63547951 2.63332665 2.6361961 2.63260801 2.62176583 2.62394369 2.63834279 2.63834279 2.63834279 2.6419104 2.63977136 2.6483002 2.63977136 2.64404487 2.6419104 2.65183252 2.65745841 2.66095859 2.65745841 2.65324196 2.65183252 2.64900766 2.64475535 2.63905733 2.6419104 2.64475535 2.63905733 2.63476241 2.62684015 2.62103882 2.63332665 2.63260801 2.63260801 2.63188884 2.63547951 2.64048488 2.63116916 2.63116916 2.63116916 2.62972823 2.64119789 2.6361961 2.64333389 2.63762774 2.64475535 2.63547951 2.63547951 2.62756295 2.63476241 2.63044896 2.62684015 2.62466859 2.63332665 2.63188884 2.61958322 2.62972823 2.62176583 2.62900699 2.63188884 2.62828523 2.63188884 2.62103882 2.62972823 2.63691217 2.63691217 2.64900766 2.65183252 2.65112705 2.65324196 2.65112705 2.64971462 2.6461748 2.6419104 2.63977136 2.64971462 2.64119789 2.6419104 2.6426224 2.64759223 2.64546533 2.63762774 2.63476241 2.6419104 2.62900699 2.64119789 2.63834279 2.64475535 2.63977136 2.6419104 2.63188884 2.64546533 2.6419104 2.63691217 2.64475535 2.63834279 2.64688377 2.65042109 2.65183252 2.65183252 2.66583835 2.65183252 2.65464942 2.6483002 2.65324196 2.65675691 2.64900766 2.64971462 2.6483002 2.6461748 2.64546533 2.65535241 2.64688377 2.66722821 2.66025954 2.6651427 2.65605491 2.64900766 2.65112705 2.65253749 2.65605491 2.64688377 2.64404487 2.64971462 2.65885996 2.64119789 2.64333389 2.63476241 2.6426224 2.64759223 2.63905733 2.64759223 2.63834279 2.6419104 2.6426224 2.64333389 2.66235524 2.67069441 2.66653352 2.66653352 2.65535241 2.65675691 2.64971462 2.64759223 2.65745841 2.65885996 2.64759223 2.65955999 2.64759223 2.65464942 2.64546533 2.65112705 2.63977136 2.65464942 2.63762774 2.64759223 2.64546533 2.64688377 2.6426224 2.6361961 2.62539297 2.64546533 2.62972823 2.6461748 2.64475535 2.64546533 2.64475535 2.63547951 2.64475535 2.63905733 2.6426224 2.63762774 2.6419104 2.65605491 2.65885996 2.65535241 2.65042109 2.64688377 2.64404487 2.64404487 2.64475535 2.64048488 2.64475535 2.63977136 2.64475535 2.65535241 2.66653352 2.6483002 2.65394594 2.65394594 2.65745841 2.66444656 2.65183252 2.66305284 2.65745841 2.65464942 2.67138622 2.67483807 2.66165716 2.67000213 2.66374994 2.66025954 2.66165716 2.65605491 2.65815943 2.65745841 2.65745841 2.6426224 2.65464942 2.64688377 2.65675691 2.65745841 2.65042109 2.64404487 2.64333389 2.65464942 2.65605491 2.65675691 2.65535241 2.64900766 2.65955999 2.66235524 2.66305284 2.68444034 2.66930937 2.66165716 2.66095859 2.66305284 2.65885996 2.65535241 2.66722821 2.67069441 2.66653352 2.66374994 2.66930937 2.65955999 2.66792241 2.66095859 2.66861613 2.66930937 2.66025954 2.66444656 2.65464942 2.65042109 2.65324196 2.66583835 2.6651427 2.66305284 2.65253749 2.65464942 2.64971462 2.63905733 2.63977136 2.63476241 2.63905733 2.63404479 2.6483002 2.65885996 2.65745841 2.66025954 2.65183252 2.65183252 2.6461748 2.64546533 2.64119789 2.64048488 2.65042109 2.63905733 2.64900766 2.65885996 2.63476241 2.65675691 2.65745841 2.65464942 2.65955999 2.65324196 2.65253749 2.65675691 2.66583835 2.6651427 2.65955999 2.67000213 2.68784749 2.67000213 2.66305284 2.64688377 2.66235524 2.67138622 2.6651427 2.65605491 2.66861613 2.6651427 2.65745841 2.65535241 2.66930937 2.65675691 2.65324196 2.65394594 2.65183252 2.66025954 2.66165716 2.65042109 2.64971462 2.65885996 2.66095859 2.65815943 2.66095859 2.67138622 2.66235524 2.66095859 2.66930937 2.65885996 2.66444656 2.67069441 2.67414865 2.67759099 2.67621548 2.67759099 2.69665216 2.67827804 2.67965073 2.68033636 2.68033636 2.68580459 2.68102153 2.66930937 2.66861613 2.66722821 2.67483807 2.67069441 2.68375751 2.65815943 2.65885996 2.65535241 2.65885996 2.65745841 2.65815943 2.65675691 2.66025954 2.66165716 2.6651427 2.65394594 2.67345876 2.67138622 2.67414865 2.66025954 2.66095859 2.65885996 2.6651427 2.65955999 2.65394594 2.65394594 2.65253749 2.66583835 2.66722821 2.67827804 2.66861613 2.67207754 2.67069441 2.67138622 2.67069441 2.67069441 2.66930937 2.68648602 2.67207754 2.69056489 2.69124308 2.69530263 2.67690347 2.67483807 2.66930937 2.67621548 2.66930937 2.67138622 2.67276839 2.67483807 2.66235524
Sample Range:
(leave blank to include all observations)
From:
To:
xgridsize
ygridsize
xbandwidth
(zero to use default)
ybandwidth
(zero to use default)
correlation
(zero to use actual correlation)
display contours
(Y/N)
Y
Y
N
display data points
(Y/N)
Y
Y
N
colors
terrain.colors
terrain.colors
rainbow
heat.colors
topo.colors
cm.colors
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') par4 <- as(par4,'numeric') par5 <- as(par5,'numeric') library('GenKern') x <- x[!is.na(y)] y <- y[!is.na(y)] y <- y[!is.na(x)] x <- x[!is.na(x)] if (par3==0) par3 <- dpik(x) if (par4==0) par4 <- dpik(y) if (par5==0) par5 <- cor(x,y) if (par1 > 500) par1 <- 500 if (par2 > 500) par2 <- 500 if (par8 == 'terrain.colors') mycol <- terrain.colors(100) if (par8 == 'rainbow') mycol <- rainbow(100) if (par8 == 'heat.colors') mycol <- heat.colors(100) if (par8 == 'topo.colors') mycol <- topo.colors(100) if (par8 == 'cm.colors') mycol <- cm.colors(100) bitmap(file='bidensity.png') op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4) image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab) if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE) if (par7=='Y') points(x,y) (r<-lm(y ~ x)) abline(r) box() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Bandwidth',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'x axis',header=TRUE) a<-table.element(a,par3) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'y axis',header=TRUE) a<-table.element(a,par4) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'correlation used in KDE',header=TRUE) a<-table.element(a,par5) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'correlation(x,y)',header=TRUE) a<-table.element(a,cor(x,y)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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