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Type 'q()' to quit R. > y <- c(9,8.6,8.8,8.5,8.3,8.2,8,7.9,8,9.3,9.6,9,8.7,8.3,8.4,7.8,7.8,7.6,7.7,7.6,7.6,8.6,8.6,8.2,7.5,7.1,7,6.9,6.6,6.3,6.1,5.9,6,7.2,7.2,6.4,6.1,5.9,6.1,5.9,5.8,5.7,5.6,5.3,5.5,6.5,6.5,6.1,5.9,5.8,6.2,6.5,6.6,6.7,6.6,6.5,6.8,7.8,7.9,7.4) > x <- c(2.86,2.55,2.28,2.26,2.57,3.08,2.76,2.51,2.87,3.14,3.12,3.16,2.48,2.57,2.88,2.63,2.38,1.69,1.96,2.19,1.87,1.6,1.63,1.22,1.21,1.49,1.64,1.66,1.77,1.82,1.78,1.28,1.29,1.37,1.12,1.51,2.24,2.94,3.09,3.46,3.64,4.39,4.15,5.21,5.8,5.91,5.39,5.46,4.72,3.14,2.63,2.32,1.93,0.62,0.6,-0.37,-1.1,-1.68,-0.78,-1.19) > 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/ > #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] -0.31 -0.27 -0.02 0.31 0.51 -0.32 -0.25 0.36 0.27 -0.02 0.04 -0.68 [13] 0.09 0.31 -0.25 -0.25 -0.69 0.27 0.23 -0.32 -0.27 0.03 -0.41 -0.01 [25] 0.28 0.15 0.02 0.11 0.05 -0.04 -0.50 0.01 0.08 -0.25 0.39 0.73 [37] 0.70 0.15 0.37 0.18 0.75 -0.24 1.06 0.59 0.11 -0.52 0.07 -0.74 [49] -1.58 -0.51 -0.31 -0.39 -1.31 -0.02 -0.97 -0.73 -0.58 0.90 -0.41 > y [1] -0.4 0.2 -0.3 -0.2 -0.1 -0.2 -0.1 0.1 1.3 0.3 -0.6 -0.3 -0.4 0.1 -0.6 [16] 0.0 -0.2 0.1 -0.1 0.0 1.0 0.0 -0.4 -0.7 -0.4 -0.1 -0.1 -0.3 -0.3 -0.2 [31] -0.2 0.1 1.2 0.0 -0.8 -0.3 -0.2 0.2 -0.2 -0.1 -0.1 -0.1 -0.3 0.2 1.0 [46] 0.0 -0.4 -0.2 -0.1 0.4 0.3 0.1 0.1 -0.1 -0.1 0.3 1.0 0.1 -0.5 > (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 49 2 52 -3 0.6397 0.5931 > (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 49 2 52 -3 0.2425 0.8662 > postscript(file="/var/www/html/rcomp/tmp/1ln5m1260625373.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 0.183 0.176 0.152 0.118 0.089 0.055 0.013 -0.027 -0.068 -0.108 -0.153 -3 -2 -1 0 1 2 3 4 5 6 7 -0.188 -0.215 -0.228 -0.232 -0.232 -0.205 -0.168 -0.150 -0.136 -0.128 -0.114 8 9 10 11 12 13 14 -0.095 -0.072 -0.065 -0.075 -0.075 -0.048 -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 0.125 0.176 0.090 -0.038 0.013 0.008 -0.027 -0.009 0.005 0.019 -0.076 -3 -2 -1 0 1 2 3 4 5 6 7 -0.079 -0.120 -0.075 -0.060 -0.050 -0.079 -0.126 -0.115 -0.012 0.016 -0.050 8 9 10 11 12 13 14 -0.126 -0.011 0.012 -0.077 -0.088 -0.030 0.047 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2uyzl1260625373.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/356kd1260625373.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/4w6cb1260625373.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/5q2nn1260625373.tab") > > system("convert tmp/1ln5m1260625373.ps tmp/1ln5m1260625373.png") > system("convert tmp/2uyzl1260625373.ps tmp/2uyzl1260625373.png") > system("convert tmp/356kd1260625373.ps tmp/356kd1260625373.png") > > > proc.time() user system elapsed 0.897 0.466 1.209