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Type 'q()' to quit R. > y <- c(1901,1395,1639,1643,1751,1797,1373,1558,1555,2061,2010,2119,1985,1963,2017,1975,1589,1679,1392,1511,1449,1767,1899,2179,2217,2049,2343,2175,1607,1702,1764,1766,1615,1953,2091,2411,2550,2351,2786,2525,2474,2332,1978,1789,1904,1997,2207,2453,1948,1384,1989,2140,2100,2045,2083,2022,1950,1422,1859,2147) > x <- c(10436,9314,9717,8997,9062,8885,9058,9095,9149,9857,9848,10269,10341,9690,10125,9349,9224,9224,9454,9347,9430,9933,10148,10677,10735,9760,10567,9333,9409,9502,9348,9319,9594,10160,10182,10810,11105,9874,10958,9311,9610,9398,9784,9425,9557,10166,10337,10770,11265,10183,10941,9628,9709,9637,9579,9741,9754,10508,10749,11079) > par8 = '2' > 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] 471 32 -56 -190 177 57 -144 29 -205 224 108 -14 -324 372 -458 [16] 201 93 -384 78 192 63 -193 99 237 -256 277 -413 223 -305 540 [31] -330 -143 43 149 -195 200 149 -326 334 -218 140 -444 521 -119 145 [46] 70 -103 > y [1] 484 -190 -46 -494 44 137 -66 -59 -188 183 171 172 -146 240 -126 [16] -182 5 349 -117 -89 20 6 40 101 -31 141 -93 517 -237 -416 [31] -191 266 -245 72 -74 -644 -365 170 412 11 87 392 128 -187 -621 [46] 227 42 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:2) + Lags(, 1:2) Model 2: ~ Lags(, 1:2) Res.Df Df F Pr(>F) 1 40 2 42 -2 0.6203 0.5429 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:2) + Lags(, 1:2) Model 2: ~ Lags(, 1:2) Res.Df Df F Pr(>F) 1 40 2 42 -2 4.7417 0.01419 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > postscript(file="/var/www/html/rcomp/tmp/182eo1260292590.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 0.305 0.289 0.318 0.093 -0.038 -0.137 -0.278 -0.296 -0.153 0.072 0.185 -3 -2 -1 0 1 2 3 4 5 6 7 0.391 0.426 0.423 0.503 0.220 0.151 0.026 -0.155 -0.186 -0.162 0.025 8 9 10 11 12 13 14 0.083 0.314 0.349 0.485 0.537 0.263 0.122 > (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 -0.025 0.116 -0.043 -0.099 0.103 -0.010 -0.020 -0.107 0.063 0.128 -0.105 -2 -1 0 1 2 3 4 5 6 7 8 0.076 -0.137 0.099 -0.192 0.320 -0.233 0.048 0.118 0.005 -0.141 -0.044 9 10 11 12 13 0.104 -0.140 0.195 -0.063 0.042 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2ksf11260292590.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/3calq1260292590.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/4grxo1260292590.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/5rm4j1260292590.tab") > > system("convert tmp/182eo1260292590.ps tmp/182eo1260292590.png") > system("convert tmp/2ksf11260292590.ps tmp/2ksf11260292590.png") > system("convert tmp/3calq1260292590.ps tmp/3calq1260292590.png") > > > proc.time() user system elapsed 0.927 0.465 1.289