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Type 'q()' to quit R. > y <- c(15.89,16.93,20.28,22.52,23.51,22.59,23.51,24.76,26.08,25.29,23.38,25.29,28.42,31.85,30.1,25.45,24.95,26.84,27.52,27.94,25.23,26.53,27.21,28.53,30.35,31.21,32.86,33.2,35.73,34.53,36.54,40.1,40.56,46.14,42.85,38.22,40.18,42.19,47.56,47.26,44.03,49.83,53.35,58.9,59.64,56.99,53.2,53.24,57.85,55.69,55.64,62.52,64.4,64.65,67.71,67.21,59.37,53.26,52.42,55.03) > x <- c(14.3,14.2,15.9,15.3,15.5,15.1,15,12.1,15.8,16.9,15.1,13.7,14.8,14.7,16,15.4,15,15.5,15.1,11.7,16.3,16.7,15,14.9,14.6,15.3,17.9,16.4,15.4,17.9,15.9,13.9,17.8,17.9,17.4,16.7,16,16.6,19.1,17.8,17.2,18.6,16.3,15.1,19.2,17.7,19.1,18,17.5,17.8,21.1,17.2,19.4,19.8,17.6,16.2,19.5,19.9,20,17.3) > par8 = '3' > 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] 13.3 13.2 14.9 14.3 14.5 14.1 14.0 11.1 14.8 15.9 14.1 12.7 13.8 13.7 15.0 [16] 14.4 14.0 14.5 14.1 10.7 15.3 15.7 14.0 13.9 13.6 14.3 16.9 15.4 14.4 16.9 [31] 14.9 12.9 16.8 16.9 16.4 15.7 15.0 15.6 18.1 16.8 16.2 17.6 15.3 14.1 18.2 [46] 16.7 18.1 17.0 16.5 16.8 20.1 16.2 18.4 18.8 16.6 15.2 18.5 18.9 19.0 16.3 > y [1] 14.89 15.93 19.28 21.52 22.51 21.59 22.51 23.76 25.08 24.29 22.38 24.29 [13] 27.42 30.85 29.10 24.45 23.95 25.84 26.52 26.94 24.23 25.53 26.21 27.53 [25] 29.35 30.21 31.86 32.20 34.73 33.53 35.54 39.10 39.56 45.14 41.85 37.22 [37] 39.18 41.19 46.56 46.26 43.03 48.83 52.35 57.90 58.64 55.99 52.20 52.24 [49] 56.85 54.69 54.64 61.52 63.40 63.65 66.71 66.21 58.37 52.26 51.42 54.03 > (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 50 2 53 -3 2.884 0.04483 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 50 2 53 -3 8.5291 0.0001125 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > postscript(file="/var/www/html/rcomp/tmp/1ocsc1260475299.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 -3 -2 0.240 0.280 0.299 0.343 0.396 0.444 0.448 0.497 0.548 0.605 0.625 0.635 0.659 -1 0 1 2 3 4 5 6 7 8 9 10 11 0.696 0.704 0.714 0.703 0.674 0.641 0.624 0.588 0.561 0.485 0.434 0.405 0.377 12 13 14 0.336 0.321 0.279 > (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 -3 -2 0.240 0.280 0.299 0.343 0.396 0.444 0.448 0.497 0.548 0.605 0.625 0.635 0.659 -1 0 1 2 3 4 5 6 7 8 9 10 11 0.696 0.704 0.714 0.703 0.674 0.641 0.624 0.588 0.561 0.485 0.434 0.405 0.377 12 13 14 0.336 0.321 0.279 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/23dqf1260475299.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/3sqh61260475299.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/4wpam1260475299.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/5hhs11260475299.tab") > > system("convert tmp/1ocsc1260475299.ps tmp/1ocsc1260475299.png") > system("convert tmp/23dqf1260475299.ps tmp/23dqf1260475299.png") > system("convert tmp/3sqh61260475299.ps tmp/3sqh61260475299.png") > > > proc.time() user system elapsed 0.921 0.472 1.073