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Type 'q()' to quit R. > y <- c(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(134.79,107.16,107.83,108.85,109.52,110.19,111.20,111.54,111.88,112.55,123.34,112.55,114.24,116.26,116.60,118.62,119.63,120.64,121.65,122.33,122.66,123.00,123.34,124.68,125.02,125.02,125.36,125.70,125.70,126.03,126.37,126.37,126.71,126.71,127.04,127.04,127.38,127.72,128.05,129.40,131.09,131.42,131.76,132.10,132.43,132.77,132.77,133.11) > 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] -27.63 0.67 1.02 0.67 0.67 1.01 0.34 0.34 0.67 10.79 [11] -10.79 1.69 2.02 0.34 2.02 1.01 1.01 1.01 0.68 0.33 [21] 0.34 0.34 1.34 0.34 0.00 0.34 0.34 0.00 0.33 0.34 [31] 0.00 0.34 0.00 0.33 0.00 0.34 0.34 0.33 1.35 1.69 [41] 0.33 0.34 0.34 0.33 0.34 0.00 0.34 > y [1] -17.68 34.57 -18.44 6.04 -6.44 12.04 -14.31 -17.15 11.11 -2.67 [11] -0.58 6.76 -20.44 53.99 -22.84 -17.69 27.60 -22.98 21.02 -34.17 [21] 11.55 5.47 -6.31 -9.78 6.27 33.51 -14.45 -7.15 6.49 -7.47 [31] 8.31 -27.24 5.78 9.15 -5.20 -6.66 -4.80 47.81 -41.55 18.67 [41] 0.80 -18.49 18.35 -36.30 21.19 4.18 -23.29 > (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 37 2 40 -3 1.1836 0.3292 > (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 37 2 40 -3 0.2539 0.858 > postscript(file="/var/www/html/rcomp/tmp/1mluh1260546682.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 -0.275 -0.148 -0.163 -0.168 -0.074 -0.142 -0.028 -0.064 -0.121 -0.073 -0.232 -2 -1 0 1 2 3 4 5 6 7 8 -0.145 -0.299 -0.219 -0.174 -0.186 -0.138 -0.051 -0.100 -0.060 -0.091 -0.066 9 10 11 12 13 -0.093 -0.103 -0.065 -0.027 0.012 > (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 -0.318 0.140 -0.012 -0.109 0.146 -0.173 0.208 -0.011 -0.106 0.219 -0.236 -2 -1 0 1 2 3 4 5 6 7 8 0.184 -0.224 0.084 0.057 -0.055 0.005 0.076 -0.057 0.040 -0.059 0.105 9 10 11 12 13 -0.112 0.040 0.008 -0.016 0.020 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2b0en1260546682.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/3pfxs1260546682.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/4f4ue1260546682.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/56chw1260546682.tab") > system("convert tmp/1mluh1260546682.ps tmp/1mluh1260546682.png") > system("convert tmp/2b0en1260546682.ps tmp/2b0en1260546682.png") > system("convert tmp/3pfxs1260546682.ps tmp/3pfxs1260546682.png") > > > proc.time() user system elapsed 0.881 0.500 1.487