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Type 'q()' to quit R. > y <- c(267413,267366,264777,258863,254844,254868,277267,285351,286602,283042,276687,277915,277128,277103,275037,270150,267140,264993,287259,291186,292300,288186,281477,282656,280190,280408,276836,275216,274352,271311,289802,290726,292300,278506,269826,265861,269034,264176,255198,253353,246057,235372,258556,260993,254663,250643,243422,247105,248541,245039,237080,237085,225554,226839,247934,248333,246969,245098,246263,255765,264319,268347,273046,273963,267430,271993,292710,295881,293299) > x <- c(21.4,26.4,26.4,29.4,34.4,24.4,26.4,25.4,31.4,27.4,27.4,29.4,32.4,26.4,22.4,19.4,21.4,23.4,23.4,25.4,28.4,27.4,21.4,17.4,24.4,26.4,22.4,14.4,18.4,25.4,29.4,26.4,26.4,20.4,26.4,29.4,33.4,32.4,35.4,34.4,36.4,32.4,34.4,31.4,27.4,27.4,30.4,32.4,32.4,27.4,31.4,29.4,27.4,25.4,26.4,23.4,18.4,22.4,17.4,17.4,11.4,9.4,6.4,0,7.8,7.9,12,16.9,12.3) > 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] 20.4 25.4 25.4 28.4 33.4 23.4 25.4 24.4 30.4 26.4 26.4 28.4 31.4 25.4 21.4 [16] 18.4 20.4 22.4 22.4 24.4 27.4 26.4 20.4 16.4 23.4 25.4 21.4 13.4 17.4 24.4 [31] 28.4 25.4 25.4 19.4 25.4 28.4 32.4 31.4 34.4 33.4 35.4 31.4 33.4 30.4 26.4 [46] 26.4 29.4 31.4 31.4 26.4 30.4 28.4 26.4 24.4 25.4 22.4 17.4 21.4 16.4 16.4 [61] 10.4 8.4 5.4 -1.0 6.8 6.9 11.0 15.9 11.3 > y [1] 267412 267365 264776 258862 254843 254867 277266 285350 286601 283041 [11] 276686 277914 277127 277102 275036 270149 267139 264992 287258 291185 [21] 292299 288185 281476 282655 280189 280407 276835 275215 274351 271310 [31] 289801 290725 292299 278505 269825 265860 269033 264175 255197 253352 [41] 246056 235371 258555 260992 254662 250642 243421 247104 248540 245038 [51] 237079 237084 225553 226838 247933 248332 246968 245097 246262 255764 [61] 264318 268346 273045 273962 267429 271992 292709 295880 293298 > (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 59 2 62 -3 3.4742 0.02152 * --- 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 59 2 62 -3 1.2044 0.3161 > postscript(file="/var/www/html/rcomp/tmp/1jysi1260373276.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 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -0.131 -0.139 -0.161 -0.194 -0.241 -0.295 -0.325 -0.335 -0.364 -0.416 -0.490 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.503 -0.479 -0.403 -0.338 -0.285 -0.221 -0.130 -0.010 0.100 0.189 0.265 7 8 9 10 11 12 13 14 15 0.303 0.369 0.441 0.552 0.594 0.586 0.551 0.530 0.544 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -0.131 -0.139 -0.161 -0.194 -0.241 -0.295 -0.325 -0.335 -0.364 -0.416 -0.490 -4 -3 -2 -1 0 1 2 3 4 5 6 -0.503 -0.479 -0.403 -0.338 -0.285 -0.221 -0.130 -0.010 0.100 0.189 0.265 7 8 9 10 11 12 13 14 15 0.303 0.369 0.441 0.552 0.594 0.586 0.551 0.530 0.544 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/23iwj1260373276.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/3vhl51260373276.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/4r2it1260373276.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/56gkl1260373276.tab") > > system("convert tmp/1jysi1260373276.ps tmp/1jysi1260373276.png") > system("convert tmp/23iwj1260373276.ps tmp/23iwj1260373276.png") > system("convert tmp/3vhl51260373276.ps tmp/3vhl51260373276.png") > > > proc.time() user system elapsed 0.932 0.469 1.432