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Type 'q()' to quit R. > y <- c(9.3,9.3,8.7,8.2,8.3,8.5,8.6,8.5,8.2,8.1,7.9,8.6,8.7,8.7,8.5,8.4,8.5,8.7,8.7,8.6,8.5,8.3,8,8.2,8.1,8.1,8,7.9,7.9,8,8,7.9,8,7.7,7.2,7.5,7.3,7,7,7,7.2,7.3,7.1,6.8,6.4,6.1,6.5,7.7,7.9,7.5,6.9,6.6,6.9,7.7,8,8,7.7,7.3,7.4,8.1) > x <- c(98.3,112.3,113.9,106.2,98.6,96.5,95.9,103.7,103.1,103.7,112.1,86.9,95,111.8,108.8,109.3,101.4,100.5,100.7,113.5,106.1,111.6,114.9,88.6,99.5,115.1,118,111.4,107.3,105.3,105.3,117.9,110.2,112.4,117.5,93,103.5,116.3,120,114.3,104.7,109.8,112.6,114.4,115.7,114.7,118.4,94.9,103.8,115.1,113.7,104,94.3,92.5,93.2,104.7,94,98.1,102.7,82.4) > par8 = '6' > 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#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] 97.3 111.3 112.9 105.2 97.6 95.5 94.9 102.7 102.1 102.7 111.1 85.9 [13] 94.0 110.8 107.8 108.3 100.4 99.5 99.7 112.5 105.1 110.6 113.9 87.6 [25] 98.5 114.1 117.0 110.4 106.3 104.3 104.3 116.9 109.2 111.4 116.5 92.0 [37] 102.5 115.3 119.0 113.3 103.7 108.8 111.6 113.4 114.7 113.7 117.4 93.9 [49] 102.8 114.1 112.7 103.0 93.3 91.5 92.2 103.7 93.0 97.1 101.7 81.4 > y [1] 8.3 8.3 7.7 7.2 7.3 7.5 7.6 7.5 7.2 7.1 6.9 7.6 7.7 7.7 7.5 7.4 7.5 7.7 7.7 [20] 7.6 7.5 7.3 7.0 7.2 7.1 7.1 7.0 6.9 6.9 7.0 7.0 6.9 7.0 6.7 6.2 6.5 6.3 6.0 [39] 6.0 6.0 6.2 6.3 6.1 5.8 5.4 5.1 5.5 6.7 6.9 6.5 5.9 5.6 5.9 6.7 7.0 7.0 6.7 [58] 6.3 6.4 7.1 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:6) + Lags(, 1:6) Model 2: ~ Lags(, 1:6) Res.Df Df F Pr(>F) 1 41 2 47 -6 3.6732 0.005192 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:6) + Lags(, 1:6) Model 2: ~ Lags(, 1:6) Res.Df Df F Pr(>F) 1 41 2 47 -6 1.2731 0.2909 > postscript(file="/var/www/html/rcomp/tmp/14ge61260531931.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 -0.235 -0.319 -0.361 -0.188 -0.092 -0.224 -0.368 -0.417 -0.352 -0.213 -0.110 -3 -2 -1 0 1 2 3 4 5 6 7 -0.197 -0.296 -0.345 -0.321 -0.012 0.059 -0.098 -0.215 -0.206 -0.069 0.122 8 9 10 11 12 13 14 0.245 0.198 0.117 0.057 0.165 0.401 0.418 > (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 -0.235 -0.319 -0.361 -0.188 -0.092 -0.224 -0.368 -0.417 -0.352 -0.213 -0.110 -3 -2 -1 0 1 2 3 4 5 6 7 -0.197 -0.296 -0.345 -0.321 -0.012 0.059 -0.098 -0.215 -0.206 -0.069 0.122 8 9 10 11 12 13 14 0.245 0.198 0.117 0.057 0.165 0.401 0.418 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2c5hf1260531931.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/3bzoh1260531931.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/456q61260531931.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/5yveq1260531931.tab") > > system("convert tmp/14ge61260531931.ps tmp/14ge61260531931.png") > system("convert tmp/2c5hf1260531931.ps tmp/2c5hf1260531931.png") > system("convert tmp/3bzoh1260531931.ps tmp/3bzoh1260531931.png") > > > proc.time() user system elapsed 0.941 0.494 3.643