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Type 'q()' to quit R. > y <- c(9,9.1,8.7,8.2,7.9,7.9,9.1,9.4,9.5,9.1,9,9.3,9.9,9.8,9.4,8.3,8,8.5,10.4,11.1,10.9,9.9,9.2,9.2,9.5,9.6,9.5,9.1,8.9,9,10.1,10.3,10.2,9.6,9.2,9.3,9.4,9.4,9.2,9,9,9,9.8,10,9.9,9.3,9,9,9.1,9.1,9.1,9.2,8.8,8.3,8.4,8.1,7.8,7.9,7.9,8) > x <- c(7.8,7.6,7.5,7.6,7.5,7.3,7.6,7.5,7.6,7.9,7.9,8.1,8.2,8,7.5,6.8,6.5,6.6,7.6,8,8,7.7,7.5,7.6,7.7,7.9,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.1,7.9,7.3,6.9,6.6,6.7,6.9,7,7.1,7.2,7.1,6.9,7,6.8,6.4,6.7,6.7,6.4,6.3,6.2,6.5) > par7 = '1' > par6 = '2' > par5 = '0.0' > par4 = '12' > par3 = '0' > par2 = '1' > par1 = '2.0' > #'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] -1.540 -0.755 0.755 -0.755 -1.480 2.235 -0.755 0.755 2.325 0.000 [11] 1.600 0.815 -1.620 -3.875 -5.005 -1.995 0.655 7.100 3.120 0.000 [21] -2.355 -1.520 0.755 0.765 1.560 -0.785 -2.295 0.000 -2.920 2.920 [31] 0.000 0.755 0.765 0.000 1.560 1.600 0.815 0.000 -0.815 -1.600 [41] -4.560 -2.840 -2.025 0.665 1.360 0.695 0.705 0.715 -0.715 -1.400 [51] 0.695 -1.380 -2.640 1.965 0.000 -1.965 -0.635 -0.625 1.905 > y [1] 0.0244808991 -0.0685439945 0.0657227248 0.0601672001 -0.0002966332 [6] -0.0276239622 -0.0614684548 -0.0244462186 -0.0090707899 0.0294916141 [11] 0.0023577804 0.0510557138 0.0105777252 0.0502353929 -0.0668459531 [16] -0.0640421576 -0.0369774749 0.0408979654 0.0539569749 0.0271772661 [21] -0.0048317516 -0.0199607426 -0.0322039415 0.0109217256 -0.0005636055 [26] 0.0320733837 0.0011846584 -0.0333964374 -0.0189797376 0.0307472741 [31] -0.0008883968 -0.0016015743 0.0116655268 -0.0205807077 0.0111654632 [36] -0.0003545471 0.0215062052 0.0114017720 -0.0773597398 -0.0140444441 [41] -0.0146854106 0.0166112658 0.0288803594 0.1029493749 -0.0424695599 [46] -0.0202110406 > postscript(file="/var/www/html/rcomp/tmp/11y611228129134.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 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 0.070 0.135 -0.055 -0.058 -0.091 0.178 0.124 0.001 -0.142 -0.267 -0.165 -2 -1 0 1 2 3 4 5 6 7 8 0.123 0.277 0.249 -0.125 -0.222 -0.264 -0.040 0.155 0.258 0.104 0.107 9 10 11 12 13 -0.069 -0.177 -0.195 -0.052 0.085 > 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/28eud1228129134.tab") > > system("convert tmp/11y611228129134.ps tmp/11y611228129134.png") > > > proc.time() user system elapsed 0.391 0.181 0.514