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Type 'q()' to quit R. > y <- c(627,696,825,677,656,785,412,352,839,729,696,641,695,638,762,635,721,854,418,367,824,687,601,676,740,691,683,594,729,731,386,331,707,715,657,653,642,643,718,654,632,731,392,344,792,852,649,629,685,617,715,715,629,916,531,357,917,828,708,858,775,785,1006,789,734,906,532,387,991,841) > x <- 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) > par8 = '11' > 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), Bivariate Granger Causality (v1.0.0) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_grangercausality.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > 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) > par8 <- as.numeric(par8) > ox <- x > oy <- y > 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] 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 > y [1] 626 695 824 676 655 784 411 351 838 728 695 640 694 637 761 [16] 634 720 853 417 366 823 686 600 675 739 690 682 593 728 730 [31] 385 330 706 714 656 652 641 642 717 653 631 730 391 343 791 [46] 851 648 628 684 616 714 714 628 915 530 356 916 827 707 857 [61] 774 784 1005 788 733 905 531 386 990 840 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:11) + Lags(, 1:11) Model 2: ~ Lags(, 1:11) Res.Df Df F Pr(>F) 1 36 2 47 -11 2.5858 0.01559 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:11) + Lags(, 1:11) Model 2: ~ Lags(, 1:11) Res.Df Df F Pr(>F) 1 36 2 47 -11 0.6469 0.7768 > postscript(file="/var/www/html/rcomp/tmp/1lqfs1261590138.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > (r <- ccf(ox,oy,main='Cross Correlation Function (raw data)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 0.091 0.085 0.089 0.068 0.019 -0.018 -0.027 -0.085 -0.101 -0.106 -0.143 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.186 -0.240 -0.256 -0.233 -0.246 -0.269 -0.240 -0.254 -0.273 -0.255 -0.238 7 8 9 10 11 12 13 14 15 -0.194 -0.175 -0.195 -0.151 -0.089 -0.092 -0.094 -0.062 -0.054 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 0.091 0.085 0.089 0.068 0.019 -0.018 -0.027 -0.085 -0.101 -0.106 -0.143 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.186 -0.240 -0.256 -0.233 -0.246 -0.269 -0.240 -0.254 -0.273 -0.255 -0.238 7 8 9 10 11 12 13 14 15 -0.194 -0.175 -0.195 -0.151 -0.089 -0.092 -0.094 -0.062 -0.054 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2smr21261590138.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > acf(ox,lag.max=round(length(x)/2),main='ACF of x (raw)') > acf(x,lag.max=round(length(x)/2),main='ACF of x (transformed and differenced)') > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/39m821261590138.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > acf(oy,lag.max=round(length(y)/2),main='ACF of y (raw)') > acf(y,lag.max=round(length(y)/2),main='ACF of y (transformed and differenced)') > par(op) > 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,'Granger Causality Test: Y = f(X)',5,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Model',header=TRUE) > a<-table.element(a,'Res.DF',header=TRUE) > a<-table.element(a,'Diff. DF',header=TRUE) > a<-table.element(a,'F',header=TRUE) > a<-table.element(a,'p-value',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Complete model',header=TRUE) > a<-table.element(a,gyx$Res.Df[1]) > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Reduced model',header=TRUE) > a<-table.element(a,gyx$Res.Df[2]) > a<-table.element(a,gyx$Df[2]) > a<-table.element(a,gyx$F[2]) > a<-table.element(a,gyx$Pr[2]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4p64g1261590139.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Model',header=TRUE) > a<-table.element(a,'Res.DF',header=TRUE) > a<-table.element(a,'Diff. DF',header=TRUE) > a<-table.element(a,'F',header=TRUE) > a<-table.element(a,'p-value',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Complete model',header=TRUE) > a<-table.element(a,gxy$Res.Df[1]) > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Reduced model',header=TRUE) > a<-table.element(a,gxy$Res.Df[2]) > a<-table.element(a,gxy$Df[2]) > a<-table.element(a,gxy$F[2]) > a<-table.element(a,gxy$Pr[2]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/5tapg1261590139.tab") > > try(system("convert tmp/1lqfs1261590138.ps tmp/1lqfs1261590138.png",intern=TRUE)) character(0) > try(system("convert tmp/2smr21261590138.ps tmp/2smr21261590138.png",intern=TRUE)) character(0) > try(system("convert tmp/39m821261590138.ps tmp/39m821261590138.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.981 0.474 4.938