R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(101.78,101.43,99.76,97.97,98.97,98.85,99.48,99.39,99.83,101.02,102.30,103.78,102.66,102.03,102.73,101.70,100.55,97.95,98.76,99.46,99.09,98.77,98.10,98.19,98.78,98.20,98.89,99.93,100.79,100.89,101.24,101.51,101.31,100.98,101.77,103.01,102.39,102.96,103.83,105.02,105.24,104.77,105.57,105.02,106.22,107.54,109.30,109.85,110.67,110.51,113.60,115.58,115.27,115.61,116.52,114.07,112.16,107.76,106.92,112.03,111.11,109.02,112.26,111.46,111.84,112.75,112.91,113.06,114.35,115.59,115.26,114.08,111.73)
> x <- c(376.974,377.632,378.205,370.861,369.167,371.551,382.842,381.903,384.502,392.058,384.359,388.884,386.586,387.495,385.705,378.67,377.367,376.911,389.827,387.82,387.267,380.575,372.402,376.74,377.795,376.126,370.804,367.98,367.866,366.121,379.421,378.519,372.423,355.072,344.693,342.892,344.178,337.606,327.103,323.953,316.532,306.307,327.225,329.573,313.761,307.836,300.074,304.198,306.122,300.414,292.133,290.616,280.244,285.179,305.486,305.957,293.886,289.441,288.776,299.149,306.532,309.914,313.468,314.901,309.16,316.15,336.544,339.196,326.738,320.838,318.62,331.533,335.378)
> par7 = 'Y'
> par6 = 'Y'
> par5 = '0'
> par4 = '0'
> par3 = '0'
> par2 = '50'
> par1 = '50'
> ylab = 'Wisselkoers Euro'
> xlab = 'Werkloosheid'
> main = 'Bivariate Kernel Density'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as(par1,'numeric')
> par2 <- as(par2,'numeric')
> par3 <- as(par3,'numeric')
> par4 <- as(par4,'numeric')
> par5 <- as(par5,'numeric')
> library('GenKern')
Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009

Loading GenKern version 1.1
Copyright Lucy and Aykroyd 2000
last update October 2004
requires KernSmooth


Package GenKern installed

> 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
> postscript(file="/var/www/html/rcomp/tmp/15r941290957254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
> image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
> if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
> if (par7=='Y') points(x,y)
> (r<-lm(y ~ x))

Call:
lm(formula = y ~ x)

Coefficients:
(Intercept)            x  
   153.9956      -0.1413  

> abline(r)
> box()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/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="/var/www/html/rcomp/tmp/2jj7d1290957254.tab") 
> 
> try(system("convert tmp/15r941290957254.ps tmp/15r941290957254.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.600   0.283   1.266