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Type 'q()' to quit R. > y <- c(100.36,100.39,100.34,100.34,100.35,100.43,100.47,100.67,100.75,100.78,100.79,100.67,100.64,100.64,100.76,100.79,100.79,100.9,100.98,101.11,101.18,101.22,101.23,101.09,101.26,101.28,101.43,101.53,101.54,101.54,101.79,102.18,102.37,102.46,102.46,102.03,102.26,102.33,102.44,102.5,102.52) > x <- c(105.02,104.43,104.63,104.93,105.87,105.66,106.76,106,107.22,107.33,107.11,108.86,107.72,107.88,108.38,107.72,108.41,109.9,111.45,112.18,113.34,113.46,114.06,115.54,116.39,115.94,116.97,115.94,115.91,116.43,116.26,116.35,117.9,117.7,117.53,117.86,117.65,116.51,115.93,115.31,115) > 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] -0.59 0.20 0.30 0.94 -0.21 1.10 -0.76 1.22 0.11 -0.22 1.75 -1.14 [13] 0.16 0.50 -0.66 0.69 1.49 1.55 0.73 1.16 0.12 0.60 1.48 0.85 [25] -0.45 1.03 -1.03 -0.03 0.52 -0.17 0.09 1.55 -0.20 -0.17 0.33 -0.21 [37] -1.14 -0.58 -0.62 -0.31 > y [1] 0.03 -0.05 0.00 0.01 0.08 0.04 0.20 0.08 0.03 0.01 -0.12 -0.03 [13] 0.00 0.12 0.03 0.00 0.11 0.08 0.13 0.07 0.04 0.01 -0.14 0.17 [25] 0.02 0.15 0.10 0.01 0.00 0.25 0.39 0.19 0.09 0.00 -0.43 0.23 [37] 0.07 0.11 0.06 0.02 > (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 36 2 37 -1 1.1392 0.2929 > (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 36 2 37 -1 0.0638 0.802 > postscript(file="/var/www/html/rcomp/tmp/1w44y1260570543.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 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 0.334 0.399 0.466 0.520 0.565 0.623 0.668 0.713 0.759 0.806 0.837 -2 -1 0 1 2 3 4 5 6 7 8 0.864 0.879 0.884 0.814 0.736 0.651 0.568 0.484 0.402 0.319 0.237 9 10 11 12 13 0.166 0.101 0.042 -0.002 -0.055 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 0.305 -0.136 0.006 0.228 -0.067 0.350 0.111 -0.059 -0.138 0.020 -0.228 -2 -1 0 1 2 3 4 5 6 7 8 0.003 0.161 -0.095 0.046 0.174 -0.013 0.152 -0.031 -0.224 -0.307 -0.193 9 10 11 12 13 -0.157 -0.011 0.005 -0.027 -0.042 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/249ja1260570543.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/3yek51260570543.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/4t4ip1260570543.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/574nh1260570543.tab") > > system("convert tmp/1w44y1260570543.ps tmp/1w44y1260570543.png") > system("convert tmp/249ja1260570543.ps tmp/249ja1260570543.png") > system("convert tmp/3yek51260570543.ps tmp/3yek51260570543.png") > > > proc.time() user system elapsed 0.899 0.469 1.114