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16.345.35
16.793.90
17.339.85
17.354.05
16.983.20
17.671.65
17.618.15
17.132.20
15.763.05
15.721.50
15.582.80
14.631.10
14.690.70
14.529.15
13.634.60
13.981.75
12.968.95
11.642.40
11.247.55
11.387.50
11.073.45
10.302.10
9.580.30
9.859.90
8.597.75
11.201.75
11.962.10
12.168.45
12.056.05
11.877.45
11.474.45
11.023.25
11.118.00
11.788.85
11.922.80
11.748.15
11.623.90
10.792.50
10.830.95
10.862.55
10.876.75
10.386.60
10.930.45
11.680.50
11.356.50
10.714.30
10.736.15
10.739.35
10.113.70
10.492.85
11.027.70
10.530.70
10.226.55
10.335.30
9.788.60
9.917.90
10.077.10
9.520.90
9.621.25
9.304.05
9.173.75
8.879.60
8.561.30
8.185.80
8.224.50
8.625.70
8.611.15
8.786.20
8.638.50
8.287.75
8.160.10
7.849.80
7.738.40
6.987.05
7.563.55
7.946.35
7.935.25
8.065.80
7.948.90
7.971.30
8.532.85
8.368.50
8.433.65
8.181.50
8.491.00
8.901.85
8.808.90
8.282.70
8.588.25
8.322.20
7.964.80
7.954.35
7.721.30
7.611.35
7.229.95
6.696.40
6.704.20
6.276.95
6.089.50
6.304.00
6.176.10
6.299.15
5.735.30
5.471.80
5.742.00
5.842.20
5.985.95
5.930.20
5.682.55
5.693.05
6.034.75
5.905.10
5.879.85
5.619.70
5.703.30
5.258.50
5.229.00
5.278.90
4.924.25
5.248.15
5.295.55
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5.199.25
4.624.30
4.832.05
5.326.60
4.943.25
5.001.00
5.482.00
5.647.40
5.560.15
5.749.50
5.833.75
5.333.25
5.505.90
6.134.50
5.862.70
6.017.70
6.029.95
5.402.40
5.367.60
5.312.50
5.086.30
5.278.00
5.249.10
4.922.30
4.882.05
5.201.05
5.032.70
4.711.70
5.083.95
4.662.10
4.636.45
4.291.10
4.448.95
3.473.95
3.020.95
2.763.65
2.874.80
2.959.15
2.755.10
2.885.60
3.921.20
4.360.00
4.332.95
4.040.55
4.870.10
5.165.90
4.734.50
5.223.50
5.137.45
6.138.60
5.762.75
5.900.65
5.021.35
4.464.00
4.528.85
4.318.30
4.295.80
4.087.90
3.821.55
3.745.30
4.082.70
3.966.40
3.954.50
3.744.10
3.588.40
3.413.90
3.143.20
3.128.20
3.071.05
3.557.60
3.402.55
3.074.70
3.001.10
2.836.55
2.652.25
2.370.95
2.601.40
2.384.65
2.312.30
2.220.60
2.087.55
1.902.50
2.035.65
2.103.25
2.057.60
2.080.50
1.958.80
1.786.90
1.745.50
1.631.75
1.632.30
1.505.60
1.483.60
1.796.10
1.771.90
1.800.30
1.809.75
1.879.75
1.615.25
1.555.90
1.417.10
1.356.55
1.185.85
1.134.15
1.006.80
934.05
978.2
1.063.40
1.041.85
1.093.50
1.050.15
951.4
963.15
1.010.60
958.9
1.057.80
1.028.80
1.084.50
1.129.55
1.142.05
1.075.40
1.059.05
1.067.15
971.9
913.85
1.053.75
1.072.85
1.107.90
1.167.90
1.125.25
1.148.20
1.351.40
1.371.70
1.263.55
1.268.15
1.172.75
1.271.65
1.394.10
1.332.85
1.471.45
1.380.45
1.406.55
1.528.45
1.654.80
1.546.20
1.480.45
1.376.15
1.325.45
1.413.10
1.412.00
1.310.15
1.187.70
1.132.30
978.2
1.078.05
981.3
966.2
884.25
817.75
824.55
904.95
852.8
931.4
941.65
1.063.15
1.159.35
1.116.90
1.060.75
963.45

6.07
5.04
5.84
5.56
4.48
4.52
4.4
4.81
5.26
5.58
5.26
5.14
5.67
4.49
3.16
3.69
5.28
5.9
5.64
5.63
5.33
5.06
5.1
5.45
5.5
6.84
7.49
9.63
8.61
7.62
6.98
6.31
5.98
8.59
8.65
8.33
7.67
6.97
6.6
5.24
4.86
5.23
5.61
5.61
5.61
3.93
3.96
3.97
4.36
4.74
5.11
4
3.97
3.24
2.89
2.52
1.79
1.08
1.09
2.21
2.61
2.62
1.86
2.23
2.59
3.35
4.14
5.3
6.46
6.13
6.59
5.86
5.51
5.53
5.91
6.32
6.72
6.32
5.14
4.35
4.37
6.1
5.7
5.79
6.28
6.3
7.17
5.86
4.12
4.98
6.3
6.75
7.23
6.49
7.02
7.08
6.7
6.73
7.24
9.13
11.47
11.06
10.7
10.75
10.85
11.06
10.68
10.24
11.44
12.06
11.62
11.17
9.55
9.6
6.14
10.31
9.84
10.05
10.16
10.22
8.65
7.57
5.32
6.49
9.34
9.39
10.06
8.99
8.43
8.62
8.72
9.41
8.82
8.82
9.3
9.47
8.33
9.7
9.82
9.88
11.25
13.73
13.91
13.33
14.86
14.86
16.22
14.97
13.51
11.49
11.64
11.72
11.89
9.29
8.63
8.7
8.03
9.63
10.45
9.7
10.45
10.45
9.77
9.02
8.33
7.69
7.75
7.81
7.87
5.47
5.51
5.51
5.51
5.51
6.4
7.26
6.45
5.69
6.61
6.67
6.72
7.56
6.72
6.53
5.95
6.92
6.4
5.94
6.33
7.27
5.93
4.65
4.57
4.57
4.37
5.57
5.33
4.18
3.63
3.45
4.06
3.32
3.74
4.96
4.17
4.17
4.37
3.78
4.17
4.57
4.81
4.61
3.19
3.02
2.83
2.23
3.49
4.13
4.35
3.72
3.07
3.29
2.89
3.1
4.16
4.41
4.66
5.12
4.06
3.86
3.43
3.2
3.6
4.06
4.3
3.86
3.89
4.16
4.66
4.69
5.17
5.19
4.94
4.23
4.89
4.23
4.73
5.19
4.04
3.39
2.5
2.28
2.53
3.02
3.25
3.48
2.74
2.75
3.5
3.99
4.95
5.24
5.01
5.54
4.83
3.61
2.62
0.47
0
0.92
2.14
3.15
3.16
5.26
7.71
8.36
8.95
8.64
9.38
15.32
79.67
18.63
16.34
15.04
14.8
12.39
10.51
8.19
8.26
9.14
9.71

par8 <- '1'
par7 <- '2'
par6 <- '1'
par5 <- '1'
par4 <- '1'
par3 <- '2'
par2 <- '1'
par1 <- '1'
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)
print(x)
print(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')