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Type 'q()' to quit R. > y <- c(142.30,120.79,121.24,104.61,119.86,117.81,91.86,117.37,112.84,101.95,120.52,102.84,137.41,118.97,125.01,118.57,130.61,116.30,99.15,110.26,107.59,107.01,113.77,93.33,147.32,124.48,106.79,134.39,111.41,132.43,98.26,109.81,115.28,108.97,99.19,105.46,138.97,124.52,117.37,123.86,116.39,124.70,97.46,103.24,112.39,107.19,100.53,95.73,143.54,101.99,120.66,121.46,102.97,121.32,85.02,106.21,110.39,87.10) > x <- c(131.76,107.16,107.83,108.85,109.52,110.19,111.20,111.54,111.88,112.55,114.24,112.55,114.24,116.26,116.60,118.62,119.63,120.64,121.65,122.33,122.66,123.00,123.34,124.68,125.02,125.02,125.36,125.70,125.70,126.03,126.37,126.37,126.71,126.71,127.04,127.04,127.38,127.72,128.05,129.40,131.09,131.42,131.76,132.10,132.43,132.77,132.77,133.11,133.45,133.78,134.12,134.46,134.79,134.79,135.13,135.13,136.82,137.15) > 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] 130.76 106.16 106.83 107.85 108.52 109.19 110.20 110.54 110.88 111.55 [11] 113.24 111.55 113.24 115.26 115.60 117.62 118.63 119.64 120.65 121.33 [21] 121.66 122.00 122.34 123.68 124.02 124.02 124.36 124.70 124.70 125.03 [31] 125.37 125.37 125.71 125.71 126.04 126.04 126.38 126.72 127.05 128.40 [41] 130.09 130.42 130.76 131.10 131.43 131.77 131.77 132.11 132.45 132.78 [51] 133.12 133.46 133.79 133.79 134.13 134.13 135.82 136.15 > y [1] 141.30 119.79 120.24 103.61 118.86 116.81 90.86 116.37 111.84 100.95 [11] 119.52 101.84 136.41 117.97 124.01 117.57 129.61 115.30 98.15 109.26 [21] 106.59 106.01 112.77 92.33 146.32 123.48 105.79 133.39 110.41 131.43 [31] 97.26 108.81 114.28 107.97 98.19 104.46 137.97 123.52 116.37 122.86 [41] 115.39 123.70 96.46 102.24 111.39 106.19 99.53 94.73 142.54 100.99 [51] 119.66 120.46 101.97 120.32 84.02 105.21 109.39 86.10 > (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 39 2 45 -6 0.6784 0.6678 > (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 39 2 45 -6 0.7881 0.5846 > postscript(file="/var/www/html/rcomp/tmp/1u0it1260545798.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 -0.094 -0.142 -0.119 -0.209 -0.158 -0.179 -0.139 -0.133 -0.171 -0.102 -0.110 -3 -2 -1 0 1 2 3 4 5 6 7 -0.153 -0.110 -0.131 -0.119 -0.165 -0.152 -0.118 -0.067 -0.068 -0.049 -0.071 8 9 10 11 12 13 14 -0.067 -0.055 -0.107 -0.071 -0.037 -0.011 -0.008 > (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 -0.094 -0.142 -0.119 -0.209 -0.158 -0.179 -0.139 -0.133 -0.171 -0.102 -0.110 -3 -2 -1 0 1 2 3 4 5 6 7 -0.153 -0.110 -0.131 -0.119 -0.165 -0.152 -0.118 -0.067 -0.068 -0.049 -0.071 8 9 10 11 12 13 14 -0.067 -0.055 -0.107 -0.071 -0.037 -0.011 -0.008 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2akxd1260545798.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/3v6yz1260545798.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/4wfwr1260545798.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/5wjfr1260545798.tab") > system("convert tmp/1u0it1260545798.ps tmp/1u0it1260545798.png") > system("convert tmp/2akxd1260545798.ps tmp/2akxd1260545798.png") > system("convert tmp/3v6yz1260545798.ps tmp/3v6yz1260545798.png") > > > proc.time() user system elapsed 0.959 0.499 2.597