R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> y <- c(96.7,98.1,100,104.9,104.9,109.5,110.8,112.3,109.3,105.3,101.7,95.4,96.4,97.6,102.4,101.6,103.8)
> x <- c(99.2,99,100,111.6,122.2,117.6,121.1,136,154.2,153.6,158.5,140.6,136.2,168,154.3,149,165.5)
> par8 = 'na.fail'
> par7 = '0'
> par6 = '0'
> par5 = '1'
> par4 = '1'
> par3 = '0'
> par2 = '0'
> par1 = '1'
> ylab = 'y'
> xlab = 'x'
> par8 <- 'na.fail'
> par7 <- '0'
> par6 <- '0'
> par5 <- '1'
> par4 <- '1'
> par3 <- '0'
> par2 <- '0'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Cross Correlation Function (v1.0.8) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_cross.wasp/
> #Source of accompanying publication: 
> #
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> par6 <- as.numeric(par6)
> par7 <- as.numeric(par7)
> if (par8=='na.fail') par8 <- na.fail else par8 <- na.pass
> ccf <- function (x, y, lag.max = NULL, type = c('correlation', 'covariance'),  plot = TRUE, na.action = na.fail, ...) {
+ type <- match.arg(type)
+ if (is.matrix(x) || is.matrix(y))
+ stop('univariate time series only')
+ X <- na.action(ts.intersect(as.ts(x), as.ts(y)))
+ colnames(X) <- c(deparse(substitute(x))[1L], deparse(substitute(y))[1L])
+ acf.out <- acf(X, lag.max = lag.max, plot = FALSE, type = type, na.action=na.action)
+ lag <- c(rev(acf.out$lag[-1, 2, 1]), acf.out$lag[, 1, 2])
+ y <- c(rev(acf.out$acf[-1, 2, 1]), acf.out$acf[, 1, 2])
+ acf.out$acf <- array(y, dim = c(length(y), 1L, 1L))
+ acf.out$lag <- array(lag, dim = c(length(y), 1L, 1L))
+ acf.out$snames <- paste(acf.out$snames, collapse = ' & ')
+ if (plot) {
+ plot(acf.out, ...)
+ return(invisible(acf.out))
+ }
+ else return(acf.out)
+ }
> 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]  98.2  98.0  99.0 110.6 121.2 116.6 120.1 135.0 153.2 152.6 157.5 139.6
[13] 135.2 167.0 153.3 148.0 164.5
> y
 [1]  95.7  97.1  99.0 103.9 103.9 108.5 109.8 111.3 108.3 104.3 100.7  94.4
[13]  95.4  96.6 101.4 100.6 102.8
> postscript(file="/var/wessaorg/rcomp/tmp/1kd071432862247.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> (r <- ccf(x,y,na.action=par8,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))

Autocorrelations of series 'X', by lag

    -9     -8     -7     -6     -5     -4     -3     -2     -1      0      1 
 0.236  0.053 -0.170 -0.336 -0.517 -0.573 -0.589 -0.453 -0.202  0.062  0.144 
     2      3      4      5      6      7      8      9 
 0.166  0.160  0.179  0.233  0.292  0.258  0.215  0.172 
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/2zb9j1432862247.tab") 
> 
> try(system("convert tmp/1kd071432862247.ps tmp/1kd071432862247.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.555   0.099   0.659