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Type 'q()' to quit R. > y <- c(92.9,107.7,103.5,91.1,79.8,71.9,82.9,90.1,100.7,90.7,108.8,44.1,93.6,107.4,96.5,93.6,76.5,76.7,84,103.3,88.5,99,105.9,44.7,94,107.1,104.8,102.5,77.7,85.2,91.3,106.5,92.4,97.5,107,51.1,98.6,102.2,114.3,99.4,72.5,92.3,99.4,85.9,109.4,97.6,104.7,56.9,86.7,108.5,103.4,86.2,71,75.9,87.1,102,88.5,87.8,100.8,50.6,85.9) > x <- c(8.1,7.7,7.5,7.6,7.8,7.8,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.2,7.9,7.3,6.9,6.6,6.7,6.9,7,7.1,7.2,7.1,6.9,7,6.8,6.4,6.7,6.6,6.4,6.3,6.2,6.5,6.8,6.8,6.4,6.1,5.8,6.1,7.2,7.3,6.9,6.1,5.8,6.2,7.1,7.7,7.9,7.7,7.4,7.5,8,8.1,8) > par8 = '1' > 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/ > #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] -0.4 -0.2 0.1 0.2 0.0 0.0 -0.3 0.0 -0.4 0.4 0.0 0.1 0.1 0.0 0.2 [16] 0.2 0.1 0.0 0.0 -0.3 -0.6 -0.4 -0.3 0.1 0.2 0.1 0.1 0.1 -0.1 -0.2 [31] 0.1 -0.2 -0.4 0.3 -0.1 -0.2 -0.1 -0.1 0.3 0.3 0.0 -0.4 -0.3 -0.3 0.3 [46] 1.1 0.1 -0.4 -0.8 -0.3 0.4 0.9 0.6 0.2 -0.2 -0.3 0.1 0.5 0.1 -0.1 > y [1] 14.8 -4.2 -12.4 -11.3 -7.9 11.0 7.2 10.6 -10.0 18.1 -64.7 49.5 [13] 13.8 -10.9 -2.9 -17.1 0.2 7.3 19.3 -14.8 10.5 6.9 -61.2 49.3 [25] 13.1 -2.3 -2.3 -24.8 7.5 6.1 15.2 -14.1 5.1 9.5 -55.9 47.5 [37] 3.6 12.1 -14.9 -26.9 19.8 7.1 -13.5 23.5 -11.8 7.1 -47.8 29.8 [49] 21.8 -5.1 -17.2 -15.2 4.9 11.2 14.9 -13.5 -0.7 13.0 -50.2 35.3 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:1) + Lags(, 1:1) Model 2: ~ Lags(, 1:1) Res.Df Df F Pr(>F) 1 56 2 57 -1 7.4615 0.008415 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:1) + Lags(, 1:1) Model 2: ~ Lags(, 1:1) Res.Df Df F Pr(>F) 1 56 2 57 -1 0.6985 0.4068 > postscript(file="/var/www/html/rcomp/tmp/1xcwm1260561788.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 0.141 0.012 0.003 -0.039 0.096 0.157 0.092 -0.038 -0.158 -0.178 -0.105 -3 -2 -1 0 1 2 3 4 5 6 7 0.013 0.052 -0.174 -0.228 -0.211 -0.053 0.027 0.006 -0.112 -0.222 -0.182 8 9 10 11 12 13 14 -0.085 0.067 0.072 -0.144 -0.179 -0.118 0.040 > (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 0.245 -0.189 -0.046 -0.115 0.061 0.186 0.063 -0.028 -0.161 -0.109 -0.043 -3 -2 -1 0 1 2 3 4 5 6 7 0.130 0.375 -0.267 -0.095 -0.134 0.023 0.164 0.131 -0.033 -0.183 -0.058 8 9 10 11 12 13 14 -0.066 0.179 0.276 -0.261 -0.096 -0.085 0.002 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2fb371260561788.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/37r7k1260561788.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/4x1s31260561788.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/5pp5w1260561788.tab") > > system("convert tmp/1xcwm1260561788.ps tmp/1xcwm1260561788.png") > system("convert tmp/2fb371260561788.ps tmp/2fb371260561788.png") > system("convert tmp/37r7k1260561788.ps tmp/37r7k1260561788.png") > > > proc.time() user system elapsed 0.926 0.477 1.132