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Type 'q()' to quit R. > y <- c(267413,267366,264777,258863,254844,254868,277267,285351,286602,283042,276687,277915,277128,277103,275037,270150,267140,264993,287259,291186,292300,288186,281477,282656,280190,280408,276836,275216,274352,271311,289802,290726,292300,278506,269826,265861,269034,264176,255198,253353,246057,235372,258556,260993,254663,250643,243422,247105,248541,245039,237080,237085,225554,226839,247934,248333,246969,245098,246263,255765,264319,268347,273046,273963,267430,271993,292710,295881,293299) > x <- c(21.4,26.4,26.4,29.4,34.4,24.4,26.4,25.4,31.4,27.4,27.4,29.4,32.4,26.4,22.4,19.4,21.4,23.4,23.4,25.4,28.4,27.4,21.4,17.4,24.4,26.4,22.4,14.4,18.4,25.4,29.4,26.4,26.4,20.4,26.4,29.4,33.4,32.4,35.4,34.4,36.4,32.4,34.4,31.4,27.4,27.4,30.4,32.4,32.4,27.4,31.4,29.4,27.4,25.4,26.4,23.4,18.4,22.4,17.4,17.4,11.4,9.4,6.4,0,7.8,7.9,12,16.9,12.3) > 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] -11.0 -4.0 -6.0 -3.0 12.0 -2.0 3.0 -3.0 3.0 -6.0 -6.0 4.0 [13] 8.0 0.0 -5.0 2.0 5.0 4.0 -5.0 -3.0 -5.0 12.0 7.0 -3.0 [25] -3.0 7.0 7.0 -2.0 -11.0 -2.0 0.0 -4.0 6.0 -3.0 -1.0 -4.0 [37] -4.0 1.0 -1.0 -4.0 2.0 -1.0 0.0 -1.0 4.0 -8.0 -2.0 -6.0 [49] 3.0 -7.0 -4.4 9.8 2.1 3.1 7.9 0.4 > y [1] 22 523 1027 1009 -2171 -133 -4157 -137 -554 -354 -49 -1679 [13] 243 -1506 3267 2146 -894 -3775 -3003 460 -9680 -1971 -5144 5639 [25] -5076 -5406 -225 -6432 -7644 4693 1513 -7904 9774 1459 7648 -1737 [37] 1356 1019 1850 -4235 11970 -2089 -2038 4966 2149 8386 5819 7118 [49] 7530 12658 912 4998 3278 -378 2772 -1218 > (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 46 2 49 -3 0.2493 0.8614 > (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 46 2 49 -3 2.5195 0.06962 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > postscript(file="/var/www/html/rcomp/tmp/16m821260375518.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 -0.131 -0.139 -0.161 -0.194 -0.241 -0.295 -0.325 -0.335 -0.364 -0.416 -0.490 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.503 -0.479 -0.403 -0.338 -0.285 -0.221 -0.130 -0.010 0.100 0.189 0.265 7 8 9 10 11 12 13 14 15 0.303 0.369 0.441 0.552 0.594 0.586 0.551 0.530 0.544 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -0.146 -0.034 -0.152 0.170 -0.077 -0.179 0.164 -0.001 -0.092 -0.188 -0.136 -3 -2 -1 0 1 2 3 4 5 6 7 -0.041 -0.122 -0.155 -0.011 -0.214 0.003 0.162 0.006 -0.096 0.114 0.066 8 9 10 11 12 13 14 0.243 -0.026 0.019 0.182 -0.035 -0.111 0.153 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2p1le1260375518.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/3fj1r1260375518.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/4ls8a1260375518.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/5j2ye1260375518.tab") > > system("convert tmp/16m821260375518.ps tmp/16m821260375518.png") > system("convert tmp/2p1le1260375518.ps tmp/2p1le1260375518.png") > system("convert tmp/3fj1r1260375518.ps tmp/3fj1r1260375518.png") > > > proc.time() user system elapsed 0.914 0.460 2.030