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(2350.44,2440.25,2408.64,2472.81,2407.6,2454.62,2448.05,2497.84,2645.64,2756.76,2849.27,2921.44,2981.85,3080.58,3106.22,3119.31,3061.26,3097.31,3161.69,3257.16,3277.01,3295.32,3363.99,3494.17,3667.03,3813.06,3917.96,3895.51,3801.06,3570.12,3701.61,3862.27,3970.1,4138.52,4199.75,4290.89,4443.91,4502.64,4356.98,4591.27,4696.96,4621.4,4562.84,4202.52,4296.49,4435.23,4105.18,4116.68,3844.49,3720.98,3674.4,3857.62,3801.06,3504.37,3032.6,3047.03,2962.34,2197.82,2014.45,1862.83,1905.41,1810.99,1670.07,1864.44,2052.02,2029.6,2070.83,2293.41,2443.27,2513.17,2466.92,2502.66,2539.91)
> x <- c(10570,10297,10635,10872,10296,10383,10431,10574,10653,10805,10872,10625,10407,10463,10556,10646,10702,11353,11346,11451,11964,12574,13031,13812,14544,14931,14886,16005,17064,15168,16050,15839,15137,14954,15648,15305,15579,16348,15928,16171,15937,15713,15594,15683,16438,17032,17696,17745,19394,20148,20108,18584,18441,18391,19178,18079,18483,19644,19195,19650,20830,23595,22937,21814,21928,21777,21383,21467,22052,22680,24320,24977,25204)
> 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] 10569 10296 10634 10871 10295 10382 10430 10573 10652 10804 10871 10624
[13] 10406 10462 10555 10645 10701 11352 11345 11450 11963 12573 13030 13811
[25] 14543 14930 14885 16004 17063 15167 16049 15838 15136 14953 15647 15304
[37] 15578 16347 15927 16170 15936 15712 15593 15682 16437 17031 17695 17744
[49] 19393 20147 20107 18583 18440 18390 19177 18078 18482 19643 19194 19649
[61] 20829 23594 22936 21813 21927 21776 21382 21466 22051 22679 24319 24976
[73] 25203
> y
 [1] 2349.44 2439.25 2407.64 2471.81 2406.60 2453.62 2447.05 2496.84 2644.64
[10] 2755.76 2848.27 2920.44 2980.85 3079.58 3105.22 3118.31 3060.26 3096.31
[19] 3160.69 3256.16 3276.01 3294.32 3362.99 3493.17 3666.03 3812.06 3916.96
[28] 3894.51 3800.06 3569.12 3700.61 3861.27 3969.10 4137.52 4198.75 4289.89
[37] 4442.91 4501.64 4355.98 4590.27 4695.96 4620.40 4561.84 4201.52 4295.49
[46] 4434.23 4104.18 4115.68 3843.49 3719.98 3673.40 3856.62 3800.06 3503.37
[55] 3031.60 3046.03 2961.34 2196.82 2013.45 1861.83 1904.41 1809.99 1669.07
[64] 1863.44 2051.02 2028.60 2069.83 2292.41 2442.27 2512.17 2465.92 2501.66
[73] 2538.91
> postscript(file="/var/www/html/rcomp/tmp/1c4di1293046403.ps",horizontal=F,onefile=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

   -15    -14    -13    -12    -11    -10     -9     -8     -7     -6     -5 
-0.364 -0.356 -0.352 -0.344 -0.341 -0.334 -0.323 -0.303 -0.279 -0.257 -0.240 
    -4     -3     -2     -1      0      1      2      3      4      5      6 
-0.222 -0.203 -0.194 -0.191 -0.181 -0.160 -0.142 -0.120 -0.095 -0.066 -0.035 
     7      8      9     10     11     12     13     14     15 
 0.002  0.047  0.092  0.135  0.183  0.232  0.277  0.327  0.374 
> 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/2tfsw1293046403.tab") 
> 
> try(system("convert tmp/1c4di1293046403.ps tmp/1c4di1293046403.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.391   0.184   0.806