R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(255
+ ,280.2
+ ,299.9
+ ,339.2
+ ,374.2
+ ,393.5
+ ,389.2
+ ,381.7
+ ,375.2
+ ,369
+ ,357.4
+ ,352.1
+ ,346.5
+ ,342.9
+ ,340.3
+ ,328.3
+ ,322.9
+ ,314.3
+ ,308.9
+ ,294
+ ,285.6
+ ,281.2
+ ,280.3
+ ,278.8
+ ,274.5
+ ,270.4
+ ,263.4
+ ,259.9
+ ,258
+ ,262.7
+ ,284.7
+ ,311.3
+ ,322.1
+ ,327
+ ,331.3
+ ,333.3
+ ,321.4
+ ,327
+ ,320
+ ,314.7
+ ,316.7
+ ,314.4
+ ,321.3
+ ,318.2
+ ,307.2
+ ,301.3
+ ,287.5
+ ,277.7
+ ,274.4
+ ,258.8
+ ,253.3
+ ,251
+ ,248.4
+ ,249.5
+ ,246.1
+ ,244.5
+ ,243.6
+ ,244
+ ,240.8
+ ,249.8
+ ,248
+ ,259.4
+ ,260.5
+ ,260.8
+ ,261.3
+ ,259.5
+ ,256.6
+ ,257.9
+ ,256.5
+ ,254.2
+ ,253.3
+ ,253.8
+ ,255.5
+ ,257.1
+ ,257.3
+ ,253.2
+ ,252.8
+ ,252
+ ,250.7
+ ,252.2
+ ,250
+ ,251
+ ,253.4
+ ,251.2
+ ,255.6
+ ,261.1
+ ,258.9
+ ,259.9
+ ,261.2
+ ,264.7
+ ,267.1
+ ,266.4
+ ,267.7
+ ,268.6
+ ,267.5
+ ,268.5
+ ,268.5
+ ,270.5
+ ,270.9
+ ,270.1
+ ,269.3
+ ,269.8
+ ,270.1
+ ,264.9
+ ,263.7
+ ,264.8
+ ,263.7
+ ,255.9
+ ,276.2
+ ,360.1
+ ,380.5
+ ,373.7
+ ,369.8
+ ,366.6
+ ,359.3
+ ,345.8
+ ,326.2
+ ,324.5
+ ,328.1
+ ,327.5
+ ,324.4
+ ,316.5
+ ,310.9
+ ,301.5
+ ,291.7
+ ,290.4
+ ,287.4
+ ,277.7
+ ,281.6
+ ,288
+ ,276
+ ,272.9
+ ,283
+ ,283.3
+ ,276.8
+ ,284.5
+ ,282.7
+ ,281.2
+ ,287.4
+ ,283.1
+ ,284
+ ,285.5
+ ,289.2
+ ,292.5
+ ,296.4
+ ,305.2
+ ,303.9
+ ,311.5
+ ,316.3
+ ,316.7
+ ,322.5
+ ,317.1
+ ,309.8
+ ,303.8
+ ,290.3
+ ,293.7
+ ,291.7
+ ,296.5
+ ,289.1
+ ,288.5
+ ,293.8
+ ,297.7
+ ,305.4
+ ,302.7
+ ,302.5
+ ,303
+ ,294.5
+ ,294.1
+ ,294.5
+ ,297.1
+ ,289.4
+ ,292.4
+ ,287.9
+ ,286.6
+ ,280.5
+ ,272.4
+ ,269.2
+ ,270.6
+ ,267.3
+ ,262.5
+ ,266.8
+ ,268.8
+ ,263.1
+ ,261.2
+ ,266
+ ,262.5
+ ,265.2
+ ,261.3
+ ,253.7
+ ,249.2
+ ,239.1
+ ,236.4
+ ,235.2
+ ,245.2
+ ,246.2
+ ,247.7
+ ,251.4
+ ,253.3
+ ,254.8
+ ,250
+ ,249.3
+ ,241.5
+ ,243.3
+ ,248
+ ,253
+ ,252.9
+ ,251.5
+ ,251.6
+ ,253.5
+ ,259.8
+ ,334.1
+ ,448
+ ,445.8
+ ,445
+ ,448.2
+ ,438.2
+ ,439.8
+ ,423.4
+ ,410.8
+ ,408.4
+ ,406.7
+ ,405.9
+ ,402.7
+ ,405.1
+ ,399.6
+ ,386.5
+ ,381.4
+ ,375.2
+ ,357.7
+ ,359
+ ,355
+ ,352.7
+ ,344.4
+ ,343.8
+ ,338
+ ,339
+ ,333.3
+ ,334.4
+ ,328.3
+ ,330.7
+ ,330
+ ,331.6
+ ,351.2
+ ,389.4
+ ,410.9
+ ,442.8
+ ,462.8
+ ,466.9
+ ,461.7
+ ,439.2
+ ,430.3
+ ,416.1
+ ,402.5
+ ,397.3
+ ,403.3
+ ,395.9
+ ,387.8
+ ,378.6
+ ,377.1
+ ,370.4
+ ,362
+ ,350.3
+ ,348.2
+ ,344.6
+ ,343.5
+ ,342.8
+ ,347.6
+ ,346.6
+ ,349.5
+ ,342.1
+ ,342
+ ,342.8
+ ,339.3
+ ,348.2
+ ,333.7
+ ,334.7
+ ,354
+ ,367.7
+ ,363.3
+ ,358.4
+ ,353.1
+ ,343.1
+ ,344.6
+ ,344.4
+ ,333.9
+ ,331.7
+ ,324.3
+ ,321.2
+ ,322.4
+ ,321.7
+ ,320.5
+ ,312.8
+ ,309.7
+ ,315.6
+ ,309.7
+ ,304.6
+ ,302.5
+ ,301.5
+ ,298.8
+ ,291.3
+ ,293.6
+ ,294.6
+ ,285.9
+ ,297.6
+ ,301.1
+ ,293.8
+ ,297.7
+ ,292.9
+ ,292.1
+ ,287.2
+ ,288.2
+ ,283.8
+ ,299.9
+ ,292.4
+ ,293.3
+ ,300.8
+ ,293.7
+ ,293.1
+ ,294.4
+ ,292.1
+ ,291.9
+ ,282.5
+ ,277.9
+ ,287.5
+ ,289.2
+ ,285.6
+ ,293.2
+ ,290.8
+ ,283.1
+ ,275
+ ,287.8
+ ,287.8
+ ,287.4
+ ,284
+ ,277.8
+ ,277.6
+ ,304.9
+ ,294
+ ,300.9
+ ,324
+ ,332.9
+ ,341.6
+ ,333.4
+ ,348.2
+ ,344.7
+ ,344.7
+ ,329.3
+ ,323.5
+ ,323.2
+ ,317.4
+ ,330.1
+ ,329.2
+ ,334.9
+ ,315.8
+ ,315.4
+ ,319.6
+ ,317.3
+ ,313.8
+ ,315.8
+ ,311.3)
> x <- c(87.28
+ ,87.28
+ ,87.09
+ ,86.92
+ ,87.59
+ ,90.72
+ ,90.69
+ ,90.3
+ ,89.55
+ ,88.94
+ ,88.41
+ ,87.82
+ ,87.07
+ ,86.82
+ ,86.4
+ ,86.02
+ ,85.66
+ ,85.32
+ ,85
+ ,84.67
+ ,83.94
+ ,82.83
+ ,81.95
+ ,81.19
+ ,80.48
+ ,78.86
+ ,69.47
+ ,68.77
+ ,70.06
+ ,73.95
+ ,75.8
+ ,77.79
+ ,81.57
+ ,83.07
+ ,84.34
+ ,85.1
+ ,85.25
+ ,84.26
+ ,83.63
+ ,86.44
+ ,85.3
+ ,84.1
+ ,83.36
+ ,82.48
+ ,81.58
+ ,80.47
+ ,79.34
+ ,82.13
+ ,81.69
+ ,80.7
+ ,79.88
+ ,79.16
+ ,78.38
+ ,77.42
+ ,76.47
+ ,75.46
+ ,74.48
+ ,78.27
+ ,80.7
+ ,79.91
+ ,78.75
+ ,77.78
+ ,81.14
+ ,81.08
+ ,80.03
+ ,78.91
+ ,78.01
+ ,76.9
+ ,75.97
+ ,81.93
+ ,80.27
+ ,78.67
+ ,77.42
+ ,76.16
+ ,74.7
+ ,76.39
+ ,76.04
+ ,74.65
+ ,73.29
+ ,71.79
+ ,74.39
+ ,74.91
+ ,74.54
+ ,73.08
+ ,72.75
+ ,71.32
+ ,70.38
+ ,70.35
+ ,70.01
+ ,69.36
+ ,67.77
+ ,69.26
+ ,69.8
+ ,68.38
+ ,67.62
+ ,68.39
+ ,66.95
+ ,65.21
+ ,66.64
+ ,63.45
+ ,60.66
+ ,62.34
+ ,60.32
+ ,58.64
+ ,60.46
+ ,58.59
+ ,61.87
+ ,61.85
+ ,67.44
+ ,77.06
+ ,91.74
+ ,93.15
+ ,94.15
+ ,93.11
+ ,91.51
+ ,89.96
+ ,88.16
+ ,86.98
+ ,88.03
+ ,86.24
+ ,84.65
+ ,83.23
+ ,81.7
+ ,80.25
+ ,78.8
+ ,77.51
+ ,76.2
+ ,75.04
+ ,74
+ ,75.49
+ ,77.14
+ ,76.15
+ ,76.27
+ ,78.19
+ ,76.49
+ ,77.31
+ ,76.65
+ ,74.99
+ ,73.51
+ ,72.07
+ ,70.59
+ ,71.96
+ ,76.29
+ ,74.86
+ ,74.93
+ ,71.9
+ ,71.01
+ ,77.47
+ ,75.78
+ ,76.6
+ ,76.07
+ ,74.57
+ ,73.02
+ ,72.65
+ ,73.16
+ ,71.53
+ ,69.78
+ ,67.98
+ ,69.96
+ ,72.16
+ ,70.47
+ ,68.86
+ ,67.37
+ ,65.87
+ ,72.16
+ ,71.34
+ ,69.93
+ ,68.44
+ ,67.16
+ ,66.01
+ ,67.25
+ ,70.91
+ ,69.75
+ ,68.59
+ ,67.48
+ ,66.31
+ ,64.81
+ ,66.58
+ ,65.97
+ ,64.7
+ ,64.7
+ ,60.94
+ ,59.08
+ ,58.42
+ ,57.77
+ ,57.11
+ ,53.31
+ ,49.96
+ ,49.4
+ ,48.84
+ ,48.3
+ ,47.74
+ ,47.24
+ ,46.76
+ ,46.29
+ ,48.9
+ ,49.23
+ ,48.53
+ ,48.03
+ ,54.34
+ ,53.79
+ ,53.24
+ ,52.96
+ ,52.17
+ ,51.7
+ ,58.55
+ ,78.2
+ ,77.03
+ ,76.19
+ ,77.15
+ ,75.87
+ ,95.47
+ ,109.67
+ ,112.28
+ ,112.01
+ ,107.93
+ ,105.96
+ ,105.06
+ ,102.98
+ ,102.2
+ ,105.23
+ ,101.85
+ ,99.89
+ ,96.23
+ ,94.76
+ ,91.51
+ ,91.63
+ ,91.54
+ ,85.23
+ ,87.83
+ ,87.38
+ ,84.44
+ ,85.19
+ ,84.03
+ ,86.73
+ ,102.52
+ ,104.45
+ ,106.98
+ ,107.02
+ ,99.26
+ ,94.45
+ ,113.44
+ ,157.33
+ ,147.38
+ ,171.89
+ ,171.95
+ ,132.71
+ ,126.02
+ ,121.18
+ ,115.45
+ ,110.48
+ ,117.85
+ ,117.63
+ ,124.65
+ ,109.59
+ ,111.27
+ ,99.78
+ ,98.21
+ ,99.2
+ ,97.97
+ ,89.55
+ ,87.91
+ ,93.34
+ ,94.42
+ ,93.2
+ ,90.29
+ ,91.46
+ ,89.98
+ ,88.35
+ ,88.41
+ ,82.44
+ ,79.89
+ ,75.69
+ ,75.66
+ ,84.5
+ ,96.73
+ ,87.48
+ ,82.39
+ ,83.48
+ ,79.31
+ ,78.16
+ ,72.77
+ ,72.45
+ ,68.46
+ ,67.62
+ ,68.76
+ ,70.07
+ ,68.55
+ ,65.3
+ ,58.96
+ ,59.17
+ ,62.37
+ ,66.28
+ ,55.62
+ ,55.23
+ ,55.85
+ ,56.75
+ ,50.89
+ ,53.88
+ ,52.95
+ ,55.08
+ ,53.61
+ ,58.78
+ ,61.85
+ ,55.91
+ ,53.32
+ ,46.41
+ ,44.57
+ ,50
+ ,50
+ ,53.36
+ ,46.23
+ ,50.45
+ ,49.07
+ ,45.85
+ ,48.45
+ ,49.96
+ ,46.53
+ ,50.51
+ ,47.58
+ ,48.05
+ ,46.84
+ ,47.67
+ ,49.16
+ ,55.54
+ ,55.82
+ ,58.22
+ ,56.19
+ ,57.77
+ ,63.19
+ ,54.76
+ ,55.74
+ ,62.54
+ ,61.39
+ ,69.6
+ ,79.23
+ ,80
+ ,93.68
+ ,107.63
+ ,100.18
+ ,97.3
+ ,90.45
+ ,80.64
+ ,80.58
+ ,75.82
+ ,85.59
+ ,89.35
+ ,89.42
+ ,104.73
+ ,95.32
+ ,89.27
+ ,90.44
+ ,86.97
+ ,79.98
+ ,81.22
+ ,87.35
+ ,83.64
+ ,82.22
+ ,94.4
+ ,102.18)
> par8 = '11'
> par7 = '0'
> par6 = '2'
> par5 = '1'
> par4 = '12'
> par3 = '0'
> par2 = '2'
> 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] -1.900000e-01  2.000000e-02  8.400000e-01  2.460000e+00 -3.160000e+00
  [6] -3.600000e-01 -3.600000e-01  1.400000e-01  8.000000e-02 -6.000000e-02
 [11] -1.600000e-01  5.000000e-01 -1.700000e-01  4.000000e-02  2.000000e-02
 [16]  2.000000e-02  2.000000e-02 -1.000000e-02 -4.000000e-01 -3.800000e-01
 [21]  2.300000e-01  1.200000e-01  5.000000e-02 -9.100000e-01 -7.770000e+00
 [26]  8.690000e+00  1.990000e+00  2.600000e+00 -2.040000e+00  1.400000e-01
 [31]  1.790000e+00 -2.280000e+00 -2.300000e-01 -5.100000e-01 -6.100000e-01
 [36] -1.140000e+00  3.600000e-01  3.440000e+00 -3.950000e+00 -6.000000e-02
 [41]  4.600000e-01 -1.400000e-01 -2.000000e-02 -2.100000e-01 -2.000000e-02
 [46]  3.920000e+00 -3.230000e+00 -5.500000e-01  1.700000e-01  1.000000e-01
 [51] -6.000000e-02 -1.800000e-01  1.000000e-02 -6.000000e-02  3.000000e-02
 [56]  4.770000e+00 -1.360000e+00 -3.220000e+00 -3.700000e-01  1.900000e-01
 [61]  4.330000e+00 -3.420000e+00 -9.900000e-01 -7.000000e-02  2.200000e-01
 [66] -2.100000e-01  1.800000e-01  6.890000e+00 -7.620000e+00  6.000000e-02
 [71]  3.500000e-01 -1.000000e-02 -2.000000e-01  3.150000e+00 -2.040000e+00
 [76] -1.040000e+00  3.000000e-02 -1.400000e-01  4.100000e+00 -2.080000e+00
 [81] -8.900000e-01 -1.090000e+00  1.130000e+00 -1.100000e+00  4.900000e-01
 [86]  9.100000e-01 -3.100000e-01 -3.100000e-01 -9.400000e-01  3.080000e+00
 [91] -9.500000e-01 -1.960000e+00  6.600000e-01  1.530000e+00 -2.210000e+00
 [96] -3.000000e-01  3.170000e+00 -4.620000e+00  4.000000e-01  4.470000e+00
[101] -3.700000e+00  3.400000e-01  3.500000e+00 -3.690000e+00  5.150000e+00
[106] -3.300000e+00  5.610000e+00  4.030000e+00  5.060000e+00 -1.327000e+01
[111] -4.100000e-01 -2.040000e+00 -5.600000e-01  5.000000e-02 -2.500000e-01
[116]  6.200000e-01  2.230000e+00 -2.840000e+00  2.000000e-01  1.700000e-01
[121] -1.100000e-01  8.000000e-02  0.000000e+00  1.600000e-01 -2.000000e-02
[126]  1.500000e-01  1.200000e-01  2.530000e+00  1.600000e-01 -2.640000e+00
[131]  1.110000e+00  1.800000e+00 -3.620000e+00  2.520000e+00 -1.480000e+00
[136] -1.000000e+00  1.800000e-01  4.000000e-02 -4.000000e-02  2.850000e+00
[141]  2.960000e+00 -5.760000e+00  1.500000e+00 -3.100000e+00  2.140000e+00
[146]  7.350000e+00 -8.150000e+00  2.510000e+00 -1.350000e+00 -9.700000e-01
[151] -5.000000e-02  1.180000e+00  8.800000e-01 -2.140000e+00 -1.200000e-01
[156] -5.000000e-02  3.780000e+00  2.200000e-01 -3.890000e+00  8.000000e-02
[161]  1.200000e-01 -1.000000e-02  7.790000e+00 -7.110000e+00 -5.900000e-01
[166] -8.000000e-02  2.100000e-01  1.300000e-01  2.390000e+00  2.420000e+00
[171] -4.820000e+00  0.000000e+00  5.000000e-02 -6.000000e-02 -3.300000e-01
[176]  3.270000e+00 -2.380000e+00 -6.600000e-01  1.270000e+00 -3.760000e+00
[181]  1.900000e+00  1.200000e+00  1.000000e-02 -1.000000e-02 -3.140000e+00
[186]  4.500000e-01  2.790000e+00  7.105427e-15  2.000000e-02 -2.000000e-02
[191]  6.000000e-02  2.000000e-02  1.000000e-02  3.080000e+00 -2.280000e+00
[196] -1.030000e+00  2.000000e-01  6.810000e+00 -6.860000e+00  7.105427e-15
[201]  2.700000e-01 -5.100000e-01  3.200000e-01  7.320000e+00  1.280000e+01
[206] -2.082000e+01  3.300000e-01  1.800000e+00 -2.240000e+00  2.088000e+01
[211] -5.400000e+00 -1.159000e+01 -2.880000e+00 -3.810000e+00  2.110000e+00
[216]  1.070000e+00 -1.180000e+00  1.300000e+00  3.810000e+00 -6.410000e+00
[221]  1.420000e+00 -1.700000e+00  2.190000e+00 -1.780000e+00  3.370000e+00
[226] -2.100000e-01 -6.220000e+00  8.910000e+00 -3.050000e+00 -2.490000e+00
[231]  3.690000e+00 -1.910000e+00  3.860000e+00  1.309000e+01 -1.386000e+01
[236]  6.000000e-01 -2.490000e+00 -7.800000e+00  2.950000e+00  2.380000e+01
[241]  2.490000e+01 -5.384000e+01  3.446000e+01 -2.445000e+01 -3.930000e+01
[246]  3.255000e+01  1.850000e+00 -8.900000e-01  7.600000e-01  1.234000e+01
[251] -7.590000e+00  7.240000e+00 -2.208000e+01  1.674000e+01 -1.317000e+01
[256]  9.920000e+00  2.560000e+00 -2.220000e+00 -7.190000e+00  6.780000e+00
[261]  7.070000e+00 -4.350000e+00 -2.300000e+00 -1.690000e+00  4.080000e+00
[266] -2.650000e+00 -1.500000e-01  1.690000e+00 -6.030000e+00  3.420000e+00
[271] -1.650000e+00  4.170000e+00  8.870000e+00  3.390000e+00 -2.148000e+01
[276]  4.160000e+00  6.180000e+00 -5.260000e+00  3.020000e+00 -4.240000e+00
[281]  5.070000e+00 -3.670000e+00  3.150000e+00  1.980000e+00  1.700000e-01
[286] -2.830000e+00 -1.730000e+00 -3.090000e+00  6.550000e+00  2.990000e+00
[291]  7.100000e-01 -1.457000e+01  1.027000e+01  1.010000e+00  2.800000e-01
[296] -6.760000e+00  8.850000e+00 -3.920000e+00  3.060000e+00 -3.600000e+00
[301]  6.640000e+00 -2.100000e+00 -9.010000e+00  3.350000e+00 -4.320000e+00
[306]  5.070000e+00  7.270000e+00 -5.430000e+00  3.360000e+00 -1.049000e+01
[311]  1.135000e+01 -5.600000e+00 -1.840000e+00  5.820000e+00 -1.090000e+00
[316] -4.940000e+00  7.410000e+00 -6.910000e+00  3.400000e+00 -1.680000e+00
[321]  2.040000e+00  6.600000e-01  4.890000e+00 -6.100000e+00  2.120000e+00
[326] -4.430000e+00  3.610000e+00  3.840000e+00 -1.385000e+01  9.410000e+00
[331]  5.820000e+00 -7.950000e+00  9.360000e+00  1.420000e+00 -8.860000e+00
[336]  1.291000e+01  2.700000e-01 -2.140000e+01  4.570000e+00 -3.970000e+00
[341] -2.960000e+00  9.750000e+00 -4.700000e+00  1.453000e+01 -6.010000e+00
[346] -3.690000e+00  1.524000e+01 -2.472000e+01  3.360000e+00  7.220000e+00
[351] -4.640000e+00 -3.520000e+00  8.230000e+00  4.890000e+00 -9.840000e+00
[356]  2.290000e+00  1.360000e+01 -4.400000e+00
> y
  [1] -5.500000e+00  1.960000e+01 -4.300000e+00 -1.570000e+01 -2.360000e+01
  [6] -3.200000e+00  1.000000e+00  3.000000e-01 -5.400000e+00  6.300000e+00
 [11] -3.000000e-01  2.000000e+00  1.000000e+00 -9.400000e+00  6.600000e+00
 [16] -3.200000e+00  3.200000e+00 -9.500000e+00  6.500000e+00  4.000000e+00
 [21]  3.500000e+00 -6.000000e-01 -2.800000e+00  2.000000e-01 -2.900000e+00
 [26]  3.500000e+00  1.600000e+00  6.600000e+00  1.730000e+01  4.600000e+00
 [31] -1.580000e+01 -5.900000e+00 -6.000000e-01 -2.300000e+00 -1.390000e+01
 [36]  1.750000e+01 -1.260000e+01  1.700000e+00  7.300000e+00 -4.300000e+00
 [41]  9.200000e+00 -1.000000e+01 -7.900000e+00  5.100000e+00 -7.900000e+00
 [46]  4.000000e+00  6.500000e+00 -1.230000e+01  1.010000e+01  3.200000e+00
 [51] -3.000000e-01  3.700000e+00 -4.500000e+00  1.800000e+00  7.000000e-01
 [56]  1.300000e+00 -3.600000e+00  1.220000e+01 -1.080000e+01  1.320000e+01
 [61] -1.030000e+01 -8.000000e-01  2.000000e-01 -2.300000e+00 -1.100000e+00
 [66]  4.200000e+00 -2.700000e+00 -9.000000e-01  1.400000e+00  1.400000e+00
 [71]  1.200000e+00 -1.000000e-01 -1.400000e+00 -4.300000e+00  3.700000e+00
 [76] -4.000000e-01 -5.000000e-01  2.800000e+00 -3.700000e+00  3.200000e+00
 [81]  1.400000e+00 -4.600000e+00  6.600000e+00  1.100000e+00 -7.700000e+00
 [86]  3.200000e+00  3.000000e-01  2.200000e+00 -1.100000e+00 -3.100000e+00
 [91]  2.000000e+00 -4.000000e-01 -2.000000e+00  2.100000e+00 -1.000000e+00
 [96]  2.000000e+00 -1.600000e+00 -1.200000e+00 -5.684342e-14  1.300000e+00
[101] -2.000000e-01 -5.500000e+00  4.000000e+00  2.300000e+00 -2.200000e+00
[106] -6.700000e+00  2.810000e+01  6.360000e+01 -6.350000e+01 -2.720000e+01
[111]  2.900000e+00  7.000000e-01 -4.100000e+00 -6.200000e+00 -6.100000e+00
[116]  1.790000e+01  5.300000e+00 -4.200000e+00 -2.500000e+00 -4.800000e+00
[121]  2.300000e+00 -3.800000e+00 -4.000000e-01  8.500000e+00 -1.700000e+00
[126] -6.700000e+00  1.360000e+01  2.500000e+00 -1.840000e+01  8.900000e+00
[131]  1.320000e+01 -9.800000e+00 -6.800000e+00  1.420000e+01 -9.500000e+00
[136]  3.000000e-01  7.700000e+00 -1.050000e+01  5.200000e+00  6.000000e-01
[141]  2.200000e+00 -4.000000e-01  6.000000e-01  4.900000e+00 -1.010000e+01
[146]  8.900000e+00 -2.800000e+00 -4.400000e+00  5.400000e+00 -1.120000e+01
[151] -1.900000e+00  1.300000e+00 -7.500000e+00  1.690000e+01 -5.400000e+00
[156]  6.800000e+00 -1.220000e+01  6.800000e+00  5.900000e+00 -1.400000e+00
[161]  3.800000e+00 -1.040000e+01  2.500000e+00  7.000000e-01 -9.000000e+00
[166]  8.100000e+00  8.000000e-01  2.200000e+00 -1.030000e+01  1.070000e+01
[171] -7.500000e+00  3.200000e+00 -4.800000e+00 -2.000000e+00  4.900000e+00
[176]  4.600000e+00 -4.700000e+00 -1.500000e+00  9.100000e+00 -2.300000e+00
[181] -7.700000e+00  3.800000e+00  6.700000e+00 -8.300000e+00  6.200000e+00
[186] -6.600000e+00 -3.700000e+00  3.100000e+00 -5.600000e+00  7.400000e+00
[191]  1.500000e+00  1.120000e+01 -9.000000e+00  5.000000e-01  2.200000e+00
[196] -1.800000e+00 -4.000000e-01 -6.300000e+00  4.100000e+00 -7.100000e+00
[201]  9.600000e+00  2.900000e+00  3.000000e-01 -5.100000e+00 -1.300000e+00
[206]  1.500000e+00  1.800000e+00  4.400000e+00  6.800000e+01  3.960000e+01
[211] -1.161000e+02  1.400000e+00  4.000000e+00 -1.320000e+01  1.160000e+01
[216] -1.800000e+01  3.800000e+00  1.020000e+01  7.000000e-01  9.000000e-01
[221] -2.400000e+00  5.600000e+00 -7.900000e+00 -7.600000e+00  8.000000e+00
[226] -1.100000e+00 -1.130000e+01  1.880000e+01 -5.300000e+00  1.700000e+00
[231] -6.000000e+00  7.700000e+00 -5.200000e+00  6.800000e+00 -6.700000e+00
[236]  6.800000e+00 -7.200000e+00  8.500000e+00 -3.100000e+00  2.300000e+00
[241]  1.800000e+01  1.860000e+01 -1.670000e+01  1.040000e+01 -1.190000e+01
[246] -1.590000e+01 -9.300000e+00 -1.730000e+01  1.360000e+01 -5.300000e+00
[251]  6.000000e-01  8.400000e+00  1.120000e+01 -1.340000e+01 -7.000000e-01
[256] -1.100000e+00  7.700000e+00 -5.200000e+00 -1.700000e+00 -3.300000e+00
[261]  9.600000e+00 -1.500000e+00  2.500000e+00  4.000000e-01  5.500000e+00
[266] -5.800000e+00  3.900000e+00 -1.030000e+01  7.300000e+00  9.000000e-01
[271] -4.300000e+00  1.240000e+01 -2.340000e+01  1.550000e+01  1.830000e+01
[276] -5.600000e+00 -1.810000e+01 -5.000000e-01 -4.000000e-01 -4.700000e+00
[281]  1.150000e+01 -1.700000e+00 -1.030000e+01  8.300000e+00 -5.200000e+00
[286]  4.300000e+00  4.300000e+00 -1.900000e+00 -5.000000e-01 -6.500000e+00
[291]  4.600000e+00  9.000000e+00 -1.180000e+01  8.000000e-01  3.000000e+00
[296]  1.100000e+00 -1.700000e+00 -4.800000e+00  9.800000e+00 -1.300000e+00
[301] -9.700000e+00  2.040000e+01 -8.200000e+00 -1.080000e+01  1.120000e+01
[306] -8.700000e+00  4.000000e+00 -4.100000e+00  5.900000e+00 -5.400000e+00
[311]  2.050000e+01 -2.360000e+01  8.400000e+00  6.600000e+00 -1.460000e+01
[316]  6.500000e+00  1.900000e+00 -3.600000e+00  2.100000e+00 -9.200000e+00
[321]  4.800000e+00  1.420000e+01 -7.900000e+00 -5.300000e+00  1.120000e+01
[326] -1.000000e+01 -5.300000e+00 -4.000000e-01  2.090000e+01 -1.280000e+01
[331] -4.000000e-01 -3.000000e+00 -2.800000e+00  6.000000e+00  2.750000e+01
[336] -3.820000e+01  1.780000e+01  1.620000e+01 -1.420000e+01 -2.000000e-01
[341] -1.690000e+01  2.300000e+01 -1.830000e+01  3.500000e+00 -1.540000e+01
[346]  9.600000e+00  5.500000e+00 -5.500000e+00  1.850000e+01 -1.360000e+01
[351]  6.600000e+00 -2.480000e+01  1.870000e+01  4.600000e+00 -6.500000e+00
[356] -1.200000e+00  5.500000e+00 -6.500000e+00
> (gyx <- grangertest(y ~ x, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:11) + Lags(, 1:11)
Model 2:  ~ Lags(, 1:11)
  Res.Df  Df      F   Pr(>F)   
1    324                       
2    335 -11 2.3716 0.007868 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> (gxy <- grangertest(x ~ y, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:11) + Lags(, 1:11)
Model 2:  ~ Lags(, 1:11)
  Res.Df  Df      F  Pr(>F)  
1    324                     
2    335 -11 2.1999 0.01425 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> postscript(file="/var/www/html/rcomp/tmp/1qqqm1260445083.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

  -22   -21   -20   -19   -18   -17   -16   -15   -14   -13   -12   -11   -10 
0.112 0.121 0.133 0.148 0.171 0.195 0.224 0.257 0.292 0.328 0.367 0.404 0.442 
   -9    -8    -7    -6    -5    -4    -3    -2    -1     0     1     2     3 
0.480 0.519 0.561 0.605 0.651 0.687 0.712 0.724 0.723 0.708 0.683 0.646 0.601 
    4     5     6     7     8     9    10    11    12    13    14    15    16 
0.561 0.526 0.494 0.466 0.436 0.405 0.370 0.340 0.315 0.293 0.277 0.265 0.253 
   17    18    19    20    21    22 
0.243 0.244 0.244 0.242 0.240 0.238 
> (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)'))

Autocorrelations of series 'X', by lag

   -22    -21    -20    -19    -18    -17    -16    -15    -14    -13    -12 
-0.041  0.009  0.037 -0.093  0.092 -0.047 -0.016  0.029  0.000 -0.036  0.054 
   -11    -10     -9     -8     -7     -6     -5     -4     -3     -2     -1 
-0.036  0.037 -0.013 -0.003 -0.021 -0.093  0.098 -0.002 -0.006  0.020  0.010 
     0      1      2      3      4      5      6      7      8      9     10 
-0.020  0.065  0.054 -0.101 -0.045  0.043 -0.042  0.026 -0.019  0.098 -0.044 
    11     12     13     14     15     16     17     18     19     20     21 
-0.066  0.084 -0.054 -0.051  0.094  0.019 -0.135  0.052  0.040 -0.013  0.000 
    22 
 0.033 
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2qeku1260445083.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/3f3z21260445083.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$Pr[2])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4nvmd1260445083.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Model',header=TRUE)
> a<-table.element(a,'Res.DF',header=TRUE)
> a<-table.element(a,'Diff. DF',header=TRUE)
> a<-table.element(a,'F',header=TRUE)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Complete model',header=TRUE)
> a<-table.element(a,gxy$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/5dpab1260445083.tab") 
> 
> system("convert tmp/1qqqm1260445083.ps tmp/1qqqm1260445083.png")
> system("convert tmp/2qeku1260445083.ps tmp/2qeku1260445083.png")
> system("convert tmp/3f3z21260445083.ps tmp/3f3z21260445083.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.140   0.491   1.530