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Type 'q()' to quit R. > y <- c(98.71,98.54,98.2,96.92,99.06,99.65,99.82,99.99,100.33,99.31,101.1,101.1,100.93,100.85,100.93,99.6,101.88,101.81,102.38,102.74,102.82,101.72,103.47,102.98,102.68,102.9,103.03,101.29,103.69,103.68,104.2,104.08,104.16,103.05,104.66,104.46,104.95,105.85,106.23,104.86,107.44,108.23,108.45,109.39,110.15,109.13,110.28,110.17,109.99,109.26,109.11,107.06,109.53,108.92,109.24,109.12,109,107.23,109.49,109.04) > x <- c(153.4,145,137.7,148.3,152.2,169.4,168.6,161.1,174.1,179,190.6,190,181.6,174.8,180.5,196.8,193.8,197,216.3,221.4,217.9,229.7,227.4,204.2,196.6,198.8,207.5,190.7,201.6,210.5,223.5,223.8,231.2,244,234.7,250.2,265.7,287.6,283.3,295.4,312.3,333.8,347.7,383.2,407.1,413.6,362.7,321.9,239.4,191,159.7,163.4,157.6,166.2,176.7,198.3,226.2,216.2,235.9,226.9) > par8 = '1' > par7 = '0' > par6 = '0' > par5 = '1' > par4 = '1' > 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/ > #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] 152.4 144.0 136.7 147.3 151.2 168.4 167.6 160.1 173.1 178.0 189.6 189.0 [13] 180.6 173.8 179.5 195.8 192.8 196.0 215.3 220.4 216.9 228.7 226.4 203.2 [25] 195.6 197.8 206.5 189.7 200.6 209.5 222.5 222.8 230.2 243.0 233.7 249.2 [37] 264.7 286.6 282.3 294.4 311.3 332.8 346.7 382.2 406.1 412.6 361.7 320.9 [49] 238.4 190.0 158.7 162.4 156.6 165.2 175.7 197.3 225.2 215.2 234.9 225.9 > y [1] 97.71 97.54 97.20 95.92 98.06 98.65 98.82 98.99 99.33 98.31 [11] 100.10 100.10 99.93 99.85 99.93 98.60 100.88 100.81 101.38 101.74 [21] 101.82 100.72 102.47 101.98 101.68 101.90 102.03 100.29 102.69 102.68 [31] 103.20 103.08 103.16 102.05 103.66 103.46 103.95 104.85 105.23 103.86 [41] 106.44 107.23 107.45 108.39 109.15 108.13 109.28 109.17 108.99 108.26 [51] 108.11 106.06 108.53 107.92 108.24 108.12 108.00 106.23 108.49 108.04 > (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 56 2 57 -1 2.9996 0.08879 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (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 56 2 57 -1 0.6926 0.4088 > postscript(file="/var/www/html/rcomp/tmp/1hs3f1260549684.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 0.454 0.517 0.563 0.589 0.592 0.597 0.596 0.589 0.576 0.581 0.589 -3 -2 -1 0 1 2 3 4 5 6 7 0.615 0.621 0.621 0.600 0.538 0.463 0.385 0.304 0.225 0.163 0.115 8 9 10 11 12 13 14 0.073 0.048 0.027 0.013 -0.002 -0.012 -0.028 > (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 0.454 0.517 0.563 0.589 0.592 0.597 0.596 0.589 0.576 0.581 0.589 -3 -2 -1 0 1 2 3 4 5 6 7 0.615 0.621 0.621 0.600 0.538 0.463 0.385 0.304 0.225 0.163 0.115 8 9 10 11 12 13 14 0.073 0.048 0.027 0.013 -0.002 -0.012 -0.028 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2p65j1260549684.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/31obm1260549684.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/4wbdf1260549685.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/5hoh71260549685.tab") > > system("convert tmp/1hs3f1260549684.ps tmp/1hs3f1260549684.png") > system("convert tmp/2p65j1260549684.ps tmp/2p65j1260549684.png") > system("convert tmp/31obm1260549684.ps tmp/31obm1260549684.png") > > > proc.time() user system elapsed 0.930 0.482 1.065