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Type 'q()' to quit R. > y <- c(3.1,3.0,2.8,2.5,1.9,1.9,1.8,2.0,2.6,2.5,2.5,1.6,1.4,0.8,1.1,1.3,1.2,1.3,1.1,1.3,1.2,1.6,1.7,1.5,0.9,1.5,1.4,1.6,1.7,1.4,1.8,1.7,1.4,1.2,1.0,1.7,2.4,2.0,2.1,2.0,1.8,2.7,2.3,1.9,2.0,2.3,2.8,2.4,2.3,2.7,2.7,2.9,3.0,2.2,2.3,2.8,2.8,2.8,2.2,2.6,2.8,2.5,2.4,2.3,1.9,1.7,2.0,2.1,1.7,1.8,1.8,1.8,1.3,1.3,1.3,1.2,1.4,2.2,2.9,3.1,3.5,3.6,4.4,4.1,5.1,5.8,5.9,5.4,5.5,4.8,3.2,2.7,2.1,1.9,0.6,0.7) > x <- c(6.3,6.0,6.2,6.4,6.8,7.5,7.5,7.6,7.6,7.4,7.3,7.1,6.9,6.8,7.5,7.6,7.8,8.0,8.1,8.2,8.3,8.2,8.0,7.9,7.6,7.6,8.3,8.4,8.4,8.4,8.4,8.6,8.9,8.8,8.3,7.5,7.2,7.4,8.8,9.3,9.3,8.7,8.2,8.3,8.5,8.6,8.5,8.2,8.1,7.9,8.6,8.7,8.7,8.5,8.4,8.5,8.7,8.7,8.6,8.5,8.3,8.0,8.2,8.1,8.1,8.0,7.9,7.9,8.0,8.0,7.9,8.0,7.7,7.2,7.5,7.3,7.0,7.0,7.0,7.2,7.3,7.1,6.8,6.4,6.1,6.5,7.7,7.9,7.5,6.9,6.6,6.9,7.7,8.0,8.0,7.7) > par8 = '3' > 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] -0.3 0.2 0.2 0.4 0.7 0.0 0.1 0.0 -0.2 -0.1 -0.2 -0.2 -0.1 0.7 0.1 [16] 0.2 0.2 0.1 0.1 0.1 -0.1 -0.2 -0.1 -0.3 0.0 0.7 0.1 0.0 0.0 0.0 [31] 0.2 0.3 -0.1 -0.5 -0.8 -0.3 0.2 1.4 0.5 0.0 -0.6 -0.5 0.1 0.2 0.1 [46] -0.1 -0.3 -0.1 -0.2 0.7 0.1 0.0 -0.2 -0.1 0.1 0.2 0.0 -0.1 -0.1 -0.2 [61] -0.3 0.2 -0.1 0.0 -0.1 -0.1 0.0 0.1 0.0 -0.1 0.1 -0.3 -0.5 0.3 -0.2 [76] -0.3 0.0 0.0 0.2 0.1 -0.2 -0.3 -0.4 -0.3 0.4 1.2 0.2 -0.4 -0.6 -0.3 [91] 0.3 0.8 0.3 0.0 -0.3 > y [1] -0.1 -0.2 -0.3 -0.6 0.0 -0.1 0.2 0.6 -0.1 0.0 -0.9 -0.2 -0.6 0.3 0.2 [16] -0.1 0.1 -0.2 0.2 -0.1 0.4 0.1 -0.2 -0.6 0.6 -0.1 0.2 0.1 -0.3 0.4 [31] -0.1 -0.3 -0.2 -0.2 0.7 0.7 -0.4 0.1 -0.1 -0.2 0.9 -0.4 -0.4 0.1 0.3 [46] 0.5 -0.4 -0.1 0.4 0.0 0.2 0.1 -0.8 0.1 0.5 0.0 0.0 -0.6 0.4 0.2 [61] -0.3 -0.1 -0.1 -0.4 -0.2 0.3 0.1 -0.4 0.1 0.0 0.0 -0.5 0.0 0.0 -0.1 [76] 0.2 0.8 0.7 0.2 0.4 0.1 0.8 -0.3 1.0 0.7 0.1 -0.5 0.1 -0.7 -1.6 [91] -0.5 -0.6 -0.2 -1.3 0.1 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 85 2 88 -3 0.1105 0.9538 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 85 2 88 -3 0.4797 0.6973 > postscript(file="/var/www/html/rcomp/tmp/15c8x1260542420.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 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 0.157 0.112 0.084 0.072 0.062 0.051 0.002 -0.080 -0.164 -0.208 -0.235 -5 -4 -3 -2 -1 0 1 2 3 4 5 -0.243 -0.250 -0.263 -0.288 -0.310 -0.315 -0.301 -0.286 -0.273 -0.246 -0.219 6 7 8 9 10 11 12 13 14 15 16 -0.186 -0.133 -0.086 -0.069 -0.075 -0.085 -0.097 -0.110 -0.113 -0.114 -0.117 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 0.035 -0.047 -0.020 -0.026 0.011 0.059 0.048 -0.022 -0.101 -0.003 -0.075 -5 -4 -3 -2 -1 0 1 2 3 4 5 -0.039 -0.120 0.004 -0.035 -0.062 -0.021 0.012 0.011 -0.083 -0.021 -0.069 6 7 8 9 10 11 12 13 14 15 16 -0.094 0.022 0.150 0.133 0.021 0.014 0.011 -0.048 -0.058 -0.001 -0.022 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2i4hv1260542420.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/361ap1260542420.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/407m41260542420.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/59phn1260542420.tab") > > system("convert tmp/15c8x1260542420.ps tmp/15c8x1260542420.png") > system("convert tmp/2i4hv1260542420.ps tmp/2i4hv1260542420.png") > system("convert tmp/361ap1260542420.ps tmp/361ap1260542420.png") > > > proc.time() user system elapsed 0.957 0.493 1.788