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Type 'q()' to quit R. > y <- c(110.8,119.3,128.1,127.6,137.9,151.4,143.6,143.4,141.9,135.2,133.1,129.6,134.1,136.8,143.5,162.5,163.1,157.2,158.8,155.4,148.5,154.2,153.3,149.4,147.9,156.0,163.0,159.1,159.5,157.3,156.4,156.6,162.4,166.8,162.6,168.1,171.3,171.0,178.7,187.5,211.4,211.6,199.4,198.7,209.3,215.5,212.8,203.2,175.7,171.0,172.5,183.5,185.4,180.9,187.3,202.0,203.3,205.8,221.5,226.6) > x <- c(149,139,135,130,127,122,117,112,113,149,157,157,147,137,132,125,123,117,114,111,112,144,150,149,134,123,116,117,111,105,102,95,93,124,130,124,115,106,105,105,101,95,93,84,87,116,120,117,109,105,107,109,109,108,107,99,103,131,137,135) > par8 = '10' > 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] -10 -4 -5 -3 -5 -5 -5 1 36 8 0 -10 -10 -5 -7 -2 -6 -3 -3 [20] 1 32 6 -1 -15 -11 -7 1 -6 -6 -3 -7 -2 31 6 -6 -9 -9 -1 [39] 0 -4 -6 -2 -9 3 29 4 -3 -8 -4 2 2 0 -1 -1 -8 4 28 [58] 6 -2 > y [1] 8.5 8.8 -0.5 10.3 13.5 -7.8 -0.2 -1.5 -6.7 -2.1 -3.5 4.5 [13] 2.7 6.7 19.0 0.6 -5.9 1.6 -3.4 -6.9 5.7 -0.9 -3.9 -1.5 [25] 8.1 7.0 -3.9 0.4 -2.2 -0.9 0.2 5.8 4.4 -4.2 5.5 3.2 [37] -0.3 7.7 8.8 23.9 0.2 -12.2 -0.7 10.6 6.2 -2.7 -9.6 -27.5 [49] -4.7 1.5 11.0 1.9 -4.5 6.4 14.7 1.3 2.5 15.7 5.1 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:10) + Lags(, 1:10) Model 2: ~ Lags(, 1:10) Res.Df Df F Pr(>F) 1 28 2 38 -10 0.5688 0.825 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:10) + Lags(, 1:10) Model 2: ~ Lags(, 1:10) Res.Df Df F Pr(>F) 1 28 2 38 -10 0.3034 0.9742 > postscript(file="/var/www/html/rcomp/tmp/1att81260488362.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 -0.420 -0.393 -0.373 -0.390 -0.420 -0.445 -0.430 -0.382 -0.361 -0.384 -0.488 -3 -2 -1 0 1 2 3 4 5 6 7 -0.592 -0.593 -0.560 -0.528 -0.469 -0.430 -0.388 -0.314 -0.233 -0.192 -0.212 8 9 10 11 12 13 14 -0.294 -0.382 -0.361 -0.281 -0.173 -0.100 -0.054 > (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 -0.191 0.001 0.101 0.069 0.022 -0.152 -0.164 0.154 0.314 0.304 0.008 -3 -2 -1 0 1 2 3 4 5 6 7 -0.251 -0.164 -0.070 -0.008 0.029 -0.021 -0.231 -0.077 0.214 0.314 0.280 8 9 10 11 12 13 14 0.046 -0.196 -0.241 -0.170 0.006 0.017 -0.077 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/23zff1260488362.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/30w1u1260488362.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/4wii21260488362.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/5avkm1260488362.tab") > system("convert tmp/1att81260488362.ps tmp/1att81260488362.png") > system("convert tmp/23zff1260488362.ps tmp/23zff1260488362.png") > system("convert tmp/30w1u1260488362.ps tmp/30w1u1260488362.png") > > > proc.time() user system elapsed 0.935 0.513 1.133