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Type 'q()' to quit R. > y <- c(151.7,121.3,133.0,119.6,122.2,117.4,106.7,87.5,81.0,110.3,87.0,55.7,146.0,137.5,138.5,135.6,107.3,99.0,91.4,68.4,82.6,98.4,71.3,47.6,130.8,113.6,125.7,113.6,97.1,104.4,91.8,75.1,89.2,110.2,78.4,68.4,122.8,129.7,159.1,139.0,102.2,113.6,81.5,77.4,87.6,101.2,87.2,64.9,133.1,118.0,135.9,125.7,108.0,128.3,84.7,86.4,92.2,95.8,92.3,54.3) > x <- c(105.2,105.2,105.6,105.6,106.2,106.3,106.4,106.9,107.2,107.3,107.3,107.4,107.55,107.87,108.37,108.38,107.92,108.03,108.14,108.3,108.64,108.66,109.04,109.03,109.03,109.54,109.75,109.83,109.65,109.82,109.95,110.12,110.15,110.2,109.99,110.14,110.14,110.81,110.97,110.99,109.73,109.81,110.02,110.18,110.21,110.25,110.36,110.51,110.64,110.95,111.18,111.19,111.69,111.7,111.83,111.77,111.73,112.01,111.86,112.04) > par8 = '1' > par7 = '1' > par6 = '1' > par5 = '1' > par4 = '12' > par3 = '1' > 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] 3.200000e-01 1.000000e-01 1.000000e-02 -1.060000e+00 1.000000e-02 [6] 1.000000e-02 -3.400000e-01 4.000000e-02 -8.000000e-02 3.800000e-01 [11] -1.100000e-01 -1.500000e-01 1.900000e-01 -2.900000e-01 7.000000e-02 [16] 2.800000e-01 6.000000e-02 2.000000e-02 1.000000e-02 -3.100000e-01 [21] 3.000000e-02 -5.900000e-01 1.600000e-01 0.000000e+00 1.600000e-01 [26] -5.000000e-02 -6.000000e-02 -1.080000e+00 -9.000000e-02 8.000000e-02 [31] -1.000000e-02 -1.421085e-14 -1.000000e-02 3.200000e-01 0.000000e+00 [36] 1.300000e-01 -3.600000e-01 7.000000e-02 -1.000000e-02 1.760000e+00 [41] -7.000000e-02 -8.000000e-02 -2.200000e-01 -7.000000e-02 2.400000e-01 [46] -2.600000e-01 3.000000e-02 > y [1] 21.9 -10.7 10.5 -30.9 -3.5 3.1 -3.8 20.7 -13.5 -3.8 7.6 -7.1 [13] -8.7 11.1 -9.2 11.8 15.6 -5.0 6.3 -0.1 5.2 -4.7 13.7 -28.8 [25] 24.1 17.3 -8.0 -20.3 4.1 -19.5 12.6 -3.9 -7.4 17.8 -12.3 13.8 [37] -22.0 -11.5 9.9 19.1 8.9 -11.5 5.8 -4.4 -10.0 10.5 -15.7 > (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 43 2 44 -1 4.1307 0.04832 * --- 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 43 2 44 -1 0.0142 0.9059 > postscript(file="/var/www/html/rcomp/tmp/1bs101260465495.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 0.025 -0.022 -0.083 -0.016 -0.022 -0.068 -0.045 -0.002 -0.009 -0.046 -0.075 -3 -2 -1 0 1 2 3 4 5 6 7 -0.094 -0.119 -0.118 -0.175 -0.127 -0.146 -0.175 -0.158 -0.111 -0.084 -0.112 8 9 10 11 12 13 14 -0.100 -0.098 -0.116 -0.106 -0.120 -0.062 -0.065 > (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 -0.034 -0.230 -0.062 0.103 0.088 0.017 -0.079 0.114 -0.016 -0.083 -0.176 -2 -1 0 1 2 3 4 5 6 7 8 0.050 0.075 0.447 -0.042 -0.004 -0.442 0.197 -0.063 -0.057 0.003 -0.049 9 10 11 12 13 0.186 -0.125 -0.036 -0.312 0.079 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2b6n91260465495.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/3oa8j1260465495.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/4m8jb1260465495.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/5s64p1260465495.tab") > > system("convert tmp/1bs101260465495.ps tmp/1bs101260465495.png") > system("convert tmp/2b6n91260465495.ps tmp/2b6n91260465495.png") > system("convert tmp/3oa8j1260465495.ps tmp/3oa8j1260465495.png") > > > proc.time() user system elapsed 0.954 0.463 1.087