R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(99.5,107.9,124.6,115,110.3,132.7,99.7,96.5,118.7,112.9,130.5,137.9,115,116.8,140.9,120.7,134.2,147.3,112.4,107.1,128.4,137.7,135,151,137.4,132.4,161.3,139.8,146,154.6,142.1,120.5)
> x <- c(97.2,102.5,113.4,109.8,104.9,126.1,80,96.8,117.2,112.3,117.3,111.1,102.2,104.3,122.9,107.6,121.3,131.5,89,104.4,128.9,135.9,133.3,121.3,120.5,120.4,137.9,126.1,133.2,146.6,103.4,117.2)
> par7 = 'Y'
> par6 = 'Y'
> par5 = '0'
> par4 = '0'
> par3 = '0'
> par2 = '50'
> par1 = '50'
> ylab = 'y'
> xlab = 'x'
> main = 'Bivariate Kernel Density'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: WESSA, (2007), Bivariate Kernel Density Estimation (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bidensity.wasp/
> #Source of accompanying publication: Lucy, D. Aykroyd, R.G. & Pollard, A.M.(2002) Non-parametric calibration for age estimation. Applied Statistics 51(2): 183-196
> #Technical description: This code makes use of the GenKern package. The dataset is based on http://exploringdata.cqu.edu.au/datasets/chirps.tab : x = temperature (degrees F) and y = chirps per second of crickets (insects).
> 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 2.22 installed
Copyright M. P. Wand 1997

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/19np71194258581.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  
    19.6894       0.9297  

> abline(r)
> box()
> dev.off()
null device 
          1 
> 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/25hj71194258581.tab") 
> 
> system("convert tmp/19np71194258581.ps tmp/19np71194258581.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.534   0.500   1.590