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Type 'q()' to quit R. > y <- c(14.2,13.5,11.9,14.6,15.6,14.1,14.9,14.2,14.6,17.2,15.4,14.3,17.5,14.5,14.4,16.6,16.7,16.6,16.9,15.7,16.4,18.4,16.9,16.5,18.3,15.1,15.7,18.1,16.8,18.9,19,18.1,17.8,21.5,17.1,18.7,19,16.4,16.9,18.6,19.3,19.4,17.6,18.6,18.1,20.4,18.1,19.6,19.9,19.2,17.8,19.2,22,21.1,19.5,22.2,20.9,22.2,23.5,21.5,24.3,22.8,20.3,23.7,23.3,19.6,18,17.3,16.8,18.2,16.5,16,18.4) > x <- c(100.2,100.4,101.4,103,109.1,111.4,114.1,121.8,127.6,129.9,128,123.5,124,127.4,127.6,128.4,131.4,135.1,134,144.5,147.3,150.9,148.7,141.4,138.9,139.8,145.6,147.9,148.5,151.1,157.5,167.5,172.3,173.5,187.5,205.5,195.1,204.5,204.5,201.7,207,206.6,210.6,211.1,215,223.9,238.2,238.9,229.6,232.2,222.1,221.6,227.3,221,213.6,243.4,253.8,265.3,268.2,268.5,266.9,268.4,250.8,231.2,192,171.4,160,148.1,144.8,147.2,155.1,161.1,169.9) > 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 1.0 1.6 6.1 2.3 2.7 7.7 5.8 2.3 -1.9 -4.5 0.5 [13] 3.4 0.2 0.8 3.0 3.7 -1.1 10.5 2.8 3.6 -2.2 -7.3 -2.5 [25] 0.9 5.8 2.3 0.6 2.6 6.4 10.0 4.8 1.2 14.0 18.0 -10.4 [37] 9.4 0.0 -2.8 5.3 -0.4 4.0 0.5 3.9 8.9 14.3 0.7 -9.3 [49] 2.6 -10.1 -0.5 5.7 -6.3 -7.4 29.8 10.4 11.5 2.9 0.3 -1.6 [61] 1.5 -17.6 -19.6 -39.2 -20.6 -11.4 -11.9 -3.3 2.4 7.9 6.0 8.8 > y [1] -0.7 -1.6 2.7 1.0 -1.5 0.8 -0.7 0.4 2.6 -1.8 -1.1 3.2 -3.0 -0.1 2.2 [16] 0.1 -0.1 0.3 -1.2 0.7 2.0 -1.5 -0.4 1.8 -3.2 0.6 2.4 -1.3 2.1 0.1 [31] -0.9 -0.3 3.7 -4.4 1.6 0.3 -2.6 0.5 1.7 0.7 0.1 -1.8 1.0 -0.5 2.3 [46] -2.3 1.5 0.3 -0.7 -1.4 1.4 2.8 -0.9 -1.6 2.7 -1.3 1.3 1.3 -2.0 2.8 [61] -1.5 -2.5 3.4 -0.4 -3.7 -1.6 -0.7 -0.5 1.4 -1.7 -0.5 2.4 > (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 38 2 49 -11 2.1266 0.04208 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:11) + Lags(, 1:11) Model 2: ~ Lags(, 1:11) Res.Df Df F Pr(>F) 1 38 2 49 -11 0.5578 0.85 > postscript(file="/var/www/html/rcomp/tmp/19osf1260469263.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 -4 -3 0.296 0.348 0.379 0.388 0.420 0.437 0.457 0.513 0.559 0.613 0.670 0.706 0.759 -2 -1 0 1 2 3 4 5 6 7 8 9 10 0.817 0.839 0.836 0.786 0.734 0.669 0.608 0.542 0.474 0.418 0.376 0.333 0.313 11 12 13 14 15 0.286 0.255 0.241 0.225 0.198 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -0.091 0.147 -0.027 0.019 0.034 -0.151 -0.130 0.083 -0.108 0.016 0.063 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.067 0.130 0.177 0.151 0.129 0.007 0.104 -0.029 0.059 0.021 -0.087 7 8 9 10 11 12 13 14 15 -0.080 0.036 -0.179 0.031 0.027 -0.135 0.009 0.083 -0.130 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2vm4w1260469263.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/31pzn1260469263.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/4jo6d1260469263.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/5xnf11260469263.tab") > > system("convert tmp/19osf1260469263.ps tmp/19osf1260469263.png") > system("convert tmp/2vm4w1260469263.ps tmp/2vm4w1260469263.png") > system("convert tmp/31pzn1260469263.ps tmp/31pzn1260469263.png") > > > proc.time() user system elapsed 0.978 0.476 1.714