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CSV
Data X:
696 641 695 638 762 635 721 854 418 367 824 687 601 676 740 691 683 594 729 731 386 331 707 715 657 653 642 643 718 654 632 731 392 344 792 852 649 629 685 617 715 715 629 916 531 357 917 828 708 858 775 785 1006 789 734 906 532 387 991 841
Data Y:
2849.27 2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.1 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.4 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.4 3857.62 3801.06 3504.37 3032.6 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41 1810.99 1670.07 1864.44 2052.02 2029.6 2070.83 2293.41 2443.27 2513.17
Box-Cox transformation parameter (X series)
1
1
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Degree (d) of non-seasonal differencing (X series)
1
0
1
2
Degree (D) of seasonal differencing (X series)
1
0
1
2
Seasonal Period
1
1
2
3
4
12
Box-Cox transformation parameter (Y series)
-0.5
1
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Degree (d) of non-seasonal differencing (Y series)
1
0
1
2
Degree (D) of seasonal differencing (Y series)
0
0
1
2
Number of non-seasonal time lags in test
2
1
2
3
4
5
6
7
8
9
10
11
Chart options
Label y-axis:
Label x-axis:
R Code
library(lmtest) 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 y (gyx <- grangertest(y ~ x, order=par8)) (gxy <- grangertest(x ~ y, order=par8)) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) (r <- ccf(ox,oy,main='Cross Correlation Function (raw data)',ylab='CCF',xlab='Lag (k)')) (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) par(op) dev.off() bitmap(file='test2.png') 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() bitmap(file='test3.png') 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() load(file='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$Pr[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Model',header=TRUE) a<-table.element(a,'Res.DF',header=TRUE) a<-table.element(a,'Diff. DF',header=TRUE) a<-table.element(a,'F',header=TRUE) a<-table.element(a,'p-value',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Complete model',header=TRUE) a<-table.element(a,gxy$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='mytable2.tab')
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R Server
Big Analytics Cloud Computing Center
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