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Type 'q()' to quit R. > y <- c(9.9,9.8,9.3,8.3,8,8.5,10.4,11.1,10.9,10,9.2,9.2,9.5,9.6,9.5,9.1,8.9,9,10.1,10.3,10.2,9.6,9.2,9.3,9.4,9.4,9.2,9,9,9,9.8,10,9.8,9.3,9,9,9.1,9.1,9.1,9.2,8.8,8.3,8.4,8.1,7.7,7.9,7.9,8,7.9,7.6,7.1,6.8,6.5,6.9,8.2,8.7,8.3,7.9,7.5,7.8) > x <- c(8.2,8,7.5,6.8,6.5,6.6,7.6,8,8.1,7.7,7.5,7.6,7.8,7.8,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.2,7.9,7.3,6.9,6.6,6.7,6.9,7,7.1,7.2,7.1,6.9,7,6.8,6.4,6.7,6.6,6.4,6.3,6.2,6.5,6.8,6.8,6.4,6.1,5.8,6.1,7.2,7.3,6.9,6.1,5.8,6.2) > par8 = '11' > par7 = '0' > par6 = '1' > par5 = '1' > par4 = '12' > par3 = '0' > 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] -0.2 -0.5 -0.7 -0.3 0.1 1.0 0.4 0.1 -0.4 -0.2 0.1 0.2 0.0 0.0 -0.3 [16] 0.0 -0.4 0.4 0.0 0.1 0.1 0.0 0.2 0.2 0.1 0.0 0.0 -0.3 -0.6 -0.4 [31] -0.3 0.1 0.2 0.1 0.1 0.1 -0.1 -0.2 0.1 -0.2 -0.4 0.3 -0.1 -0.2 -0.1 [46] -0.1 0.3 0.3 0.0 -0.4 -0.3 -0.3 0.3 1.1 0.1 -0.4 -0.8 -0.3 0.4 > y [1] -0.1 -0.5 -1.0 -0.3 0.5 1.9 0.7 -0.2 -0.9 -0.8 0.0 0.3 0.1 -0.1 -0.4 [16] -0.2 0.1 1.1 0.2 -0.1 -0.6 -0.4 0.1 0.1 0.0 -0.2 -0.2 0.0 0.0 0.8 [31] 0.2 -0.2 -0.5 -0.3 0.0 0.1 0.0 0.0 0.1 -0.4 -0.5 0.1 -0.3 -0.4 0.2 [46] 0.0 0.1 -0.1 -0.3 -0.5 -0.3 -0.3 0.4 1.3 0.5 -0.4 -0.4 -0.4 0.3 > (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 25 2 36 -11 1.6291 0.1509 > (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 25 2 36 -11 0.8644 0.5836 > postscript(file="/var/www/html/rcomp/tmp/195ez1260475405.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 0.200 0.323 0.422 0.421 0.388 0.407 0.503 0.626 0.666 0.543 0.383 0.324 0.433 -1 0 1 2 3 4 5 6 7 8 9 10 11 0.632 0.774 0.684 0.515 0.399 0.411 0.504 0.566 0.517 0.403 0.276 0.179 0.141 12 13 14 0.149 0.138 0.133 > (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 -0.112 0.040 0.326 0.118 -0.077 -0.184 -0.058 0.200 0.309 0.080 -0.317 -3 -2 -1 0 1 2 3 4 5 6 7 -0.467 -0.275 0.185 0.694 0.297 -0.123 -0.397 -0.251 0.065 0.202 0.168 8 9 10 11 12 13 14 0.058 -0.060 -0.166 -0.173 0.056 -0.034 0.011 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/28g311260475405.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/3v8261260475405.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/441nn1260475405.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/5t4yn1260475405.tab") > > system("convert tmp/195ez1260475405.ps tmp/195ez1260475405.png") > system("convert tmp/28g311260475405.ps tmp/28g311260475405.png") > system("convert tmp/3v8261260475405.ps tmp/3v8261260475405.png") > > > proc.time() user system elapsed 0.959 0.480 1.385