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Type 'q()' to quit R. > y <- c(14.3,14.2,15.9,15.3,15.5,15.1,15,12.1,15.8,16.9,15.1,13.7,14.8,14.7,16,15.4,15,15.5,15.1,11.7,16.3,16.7,15,14.9,14.6,15.3,17.9,16.4,15.4,17.9,15.9,13.9,17.8,17.9,17.4,16.7,16,16.6,19.1,17.8,17.2,18.6,16.3,15.1,19.2,17.7,19.1,18,17.5,17.8,21.1,17.2,19.4,19.8,17.6,16.2,19.5,19.9,20,17.3,18.9,18.6,21.4,18.6,19.8,20.8,19.6,17.7,19.8,22.2,20.7,17.9) > x <- c(13.4,13.5,14.8,14.3,14.3,14,13.2,12.2,14.3,15.7,14.2,14.6,14.5,14.3,15.3,14.4,13.7,14.2,13.5,11.9,14.6,15.6,14.1,14.9,14.2,14.6,17.2,15.4,14.3,17.5,14.5,14.4,16.6,16.7,16.6,16.9,15.7,16.4,18.4,16.9,16.5,18.3,15.1,15.7,18.1,16.8,18.9,19,18.1,17.8,21.5,17.1,18.7,19,16.4,16.9,18.6,19.3,19.4,17.6,18.6,18.1,20.4,18.1,19.6,19.9,19.2,17.8,19.2,22,21.1,19.5) > par8 = '1' > par7 = '1' > par6 = '0' > par5 = '1' > par4 = '12' > par3 = '1' > 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] 1.1 0.8 0.5 0.1 -0.6 0.2 0.3 -0.3 0.3 -0.1 -0.1 0.3 -0.3 0.3 1.9 [16] 1.0 0.6 3.3 1.0 2.5 2.0 1.1 2.5 2.0 1.5 1.8 1.2 1.5 2.2 0.8 [31] 0.6 1.3 1.5 0.1 2.3 2.1 2.4 1.4 3.1 0.2 2.2 0.7 1.3 1.2 0.5 [46] 2.5 0.5 -1.4 0.5 0.3 -1.1 1.0 0.9 0.9 2.8 0.9 0.6 2.7 1.7 1.9 > y [1] 0.5 0.5 0.1 0.1 -0.5 0.4 0.1 -0.4 0.5 -0.2 -0.1 1.2 -0.2 0.6 1.9 [16] 1.0 0.4 2.4 0.8 2.2 1.5 1.2 2.4 1.8 1.4 1.3 1.2 1.4 1.8 0.7 [31] 0.4 1.2 1.4 -0.2 1.7 1.3 1.5 1.2 2.0 -0.6 2.2 1.2 1.3 1.1 0.3 [46] 2.2 0.9 -0.7 1.4 0.8 0.3 1.4 0.4 1.0 2.0 1.5 0.3 2.3 0.7 0.6 > (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 0.5163 0.4754 > (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 2.0042 0.1624 > postscript(file="/var/www/html/rcomp/tmp/1eato1262160201.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 0.324 0.269 0.364 0.566 0.416 0.365 0.467 0.458 0.518 0.638 0.559 0.608 0.639 -2 -1 0 1 2 3 4 5 6 7 8 9 10 0.534 0.678 0.956 0.679 0.592 0.627 0.579 0.596 0.651 0.492 0.521 0.495 0.317 11 12 13 14 15 0.429 0.557 0.355 0.298 0.279 > (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 -0.073 -0.166 -0.113 -0.126 -0.164 0.035 0.029 -0.153 0.207 0.129 0.080 -3 -2 -1 0 1 2 3 4 5 6 7 0.424 0.258 0.099 0.877 0.156 0.275 0.507 0.208 0.112 0.254 -0.116 8 9 10 11 12 13 14 0.141 0.111 -0.204 0.019 -0.108 -0.145 0.062 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2jv0v1262160201.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/3imb81262160201.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/4y4a71262160201.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/5n6651262160201.tab") > > try(system("convert tmp/1eato1262160201.ps tmp/1eato1262160201.png",intern=TRUE)) character(0) > try(system("convert tmp/2jv0v1262160201.ps tmp/2jv0v1262160201.png",intern=TRUE)) character(0) > try(system("convert tmp/3imb81262160201.ps tmp/3imb81262160201.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.924 0.466 1.670