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Type 'q()' to quit R. > y <- c(593530,610943,612613,611324,594167,595454,590865,589379,584428,573100,567456,569028,620735,628884,628232,612117,595404,597141,593408,590072,579799,574205,572775,572942,619567,625809,619916,587625,565742,557274,560576,548854,531673,525919,511038,498662,555362,564591,541657,527070,509846,514258,516922,507561,492622,490243,469357,477580,528379,533590,517945,506174,501866,516141,528222,532638,536322,536535,523597,536214,586570,596594,580523) > x <- c(277267,285531,286602,283042,276687,277915,277128,277103,275037,270150,267140,264993,287259,291186,292300,288186,281477,282656,280190,280408,276836,275216,274352,271311,289802,290726,292300,278506,269826,265861,269034,264176,255198,253353,246057,235372,258556,260993,254663,250643,243422,247105,248541,245039,237080,237085,225554,226839,247934,248333,246969,245098,246263,255765,264319,268347,273046,273963,267430,271993,292710,295881,293299) > par8 = '3' > par7 = '1' > par6 = '1' > par5 = '1' > par4 = '12' > par3 = '1' > par2 = '1' > 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#output/ > #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] -4337 43 -554 -354 -49 -1679 243 -1506 3267 2146 -894 -3775 [13] -3003 460 -9680 -1971 -5144 5639 -5076 -5406 -225 -6432 -7644 4693 [25] 1513 -7904 9774 1459 7648 -1737 1356 1019 1850 -4235 11970 -2089 [37] -2038 4966 2149 8386 5819 7118 7530 12658 912 4998 3278 -378 [49] 2772 -1218 > y [1] -9264 -2322 -14826 444 450 856 -1850 -5322 5734 4214 [11] -1405 -5082 -1907 -5241 -16176 -5170 -10205 7035 -8386 -6908 [21] -160 -13451 -12543 10075 2987 -17041 17704 4659 12880 -638 [31] 2361 2242 3375 -6005 20599 -5901 -4018 7289 2816 12916 [41] 9863 9417 13777 18623 2592 7948 4394 -443 4813 -426 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 40 2 43 -3 2.1412 0.1102 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 40 2 43 -3 0.9123 0.4437 > postscript(file="/var/www/html/rcomp/tmp/1irto1261141821.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 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 0.169 0.323 0.471 0.482 0.439 0.426 0.462 0.540 0.601 0.619 0.612 0.633 0.705 -1 0 1 2 3 4 5 6 7 8 9 10 11 0.833 0.934 0.836 0.682 0.559 0.504 0.490 0.450 0.369 0.270 0.211 0.206 0.266 12 13 14 0.294 0.174 0.029 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -0.002 -0.186 0.319 -0.057 0.040 0.105 0.052 0.199 0.063 0.196 0.348 -2 -1 0 1 2 3 4 5 6 7 8 0.334 0.110 0.953 0.142 0.244 0.324 0.222 0.136 0.144 0.048 0.188 9 10 11 12 13 0.104 -0.072 0.344 -0.014 0.001 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2nbc91261141821.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/3w8kh1261141821.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/44jfo1261141821.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/51oiz1261141821.tab") > > try(system("convert tmp/1irto1261141821.ps tmp/1irto1261141821.png",intern=TRUE)) character(0) > try(system("convert tmp/2nbc91261141821.ps tmp/2nbc91261141821.png",intern=TRUE)) character(0) > try(system("convert tmp/3w8kh1261141821.ps tmp/3w8kh1261141821.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.938 0.489 3.154