R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(6.8,6.9,6.8,6.2,6.2,6.6,6.8,7.1,7.3,7.2,7,7,7,7.3,7.5,7.2,7.7,8,7.9,8,8,7.9,7.9,7.9,8.1,8.1,8.2,8.1,8.3,8.5,8.6,8.7,8.7,8.5,8.4,8.5,8.8,8.7,8.6,8,8.1,8.2,8.6,8.6,8.5,8.3,8.2,8.7,9.3,9.3,8.8,7.5,7.2,7.5,8.3,8.8,8.9,8.6,8.4,8.4,8.4)
> x <- c(101.2,100.5,98,106.6,90.1,96.9,125.9,112,100,123.9,79.8,83.4,113.6,112.9,104,109.9,99,106.3,128.9,111.1,102.9,130,87,87.5,117.6,103.4,110.8,112.6,102.5,112.4,135.6,105.1,127.7,137,91,90.5,122.4,123.3,124.3,120,118.1,119,142.7,123.6,129.6,151.6,110.4,99.2,130.5,136.2,129.7,128,121.6,135.8,143.8,147.5,136.2,156.6,123.3,104.5,143.6)
> par7 = '0'
> par6 = '0'
> par5 = '1'
> par4 = '12'
> par3 = '0'
> par2 = '0'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2008), Cross Correlation Function (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_cross.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> par6 <- as.numeric(par6)
> par7 <- as.numeric(par7)
> if (par1 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par1 - 1) / par1
+ }
> if (par5 == 0) {
+ y <- log(y)
+ } else {
+ y <- (y ^ par5 - 1) / par5
+ }
> if (par2 > 0) x <- diff(x,lag=1,difference=par2)
> if (par6 > 0) y <- diff(y,lag=1,difference=par6)
> if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
> if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
> x
 [1] 100.2  99.5  97.0 105.6  89.1  95.9 124.9 111.0  99.0 122.9  78.8  82.4
[13] 112.6 111.9 103.0 108.9  98.0 105.3 127.9 110.1 101.9 129.0  86.0  86.5
[25] 116.6 102.4 109.8 111.6 101.5 111.4 134.6 104.1 126.7 136.0  90.0  89.5
[37] 121.4 122.3 123.3 119.0 117.1 118.0 141.7 122.6 128.6 150.6 109.4  98.2
[49] 129.5 135.2 128.7 127.0 120.6 134.8 142.8 146.5 135.2 155.6 122.3 103.5
[61] 142.6
> y
 [1] 5.8 5.9 5.8 5.2 5.2 5.6 5.8 6.1 6.3 6.2 6.0 6.0 6.0 6.3 6.5 6.2 6.7 7.0 6.9
[20] 7.0 7.0 6.9 6.9 6.9 7.1 7.1 7.2 7.1 7.3 7.5 7.6 7.7 7.7 7.5 7.4 7.5 7.8 7.7
[39] 7.6 7.0 7.1 7.2 7.6 7.6 7.5 7.3 7.2 7.7 8.3 8.3 7.8 6.5 6.2 6.5 7.3 7.8 7.9
[58] 7.6 7.4 7.4 7.4
> postscript(file="/var/www/html/rcomp/tmp/18sbk1228299442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> (r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))

Autocorrelations of series 'X', by lag

   -14    -13    -12    -11    -10     -9     -8     -7     -6     -5     -4 
-0.071 -0.028  0.068  0.114  0.067  0.004  0.061  0.138  0.241  0.361  0.339 
    -3     -2     -1      0      1      2      3      4      5      6      7 
 0.307  0.341  0.395  0.488  0.480  0.346  0.244  0.311  0.348  0.397  0.526 
     8      9     10     11     12     13     14 
 0.478  0.372  0.424  0.397  0.393  0.400  0.304 
> 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,'Cross Correlation Function',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'Value',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
> a<-table.element(a,par1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
> a<-table.element(a,par2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
> a<-table.element(a,par3)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Period (s)',header=TRUE)
> a<-table.element(a,par4)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
> a<-table.element(a,par5)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
> a<-table.element(a,par6)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
> a<-table.element(a,par7)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'k',header=TRUE)
> a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
> a<-table.row.end(a)
> mylength <- length(r$acf)
> myhalf <- floor((mylength-1)/2)
> for (i in 1:mylength) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-myhalf-1,header=TRUE)
+ a<-table.element(a,r$acf[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/29jtb1228299442.tab") 
> 
> system("convert tmp/18sbk1228299442.ps tmp/18sbk1228299442.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.180   0.281   1.229