Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
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
Data Y:
982.32 1220.41 1167.97 1235.11 1307.34 1269.91 1632.67 1795.99 1885.28 1889.84 1903.31 1908.85 2302.54 3017.68 4285 3887.72 3006.08 3080.54 2727.06 3031.63 3294.42 2833.34 2518.1 2615.37 2680.79 2652.4 2280.52 2122.3 2192.74 2227.54 2328.21 2633.79 2709.64 2673.74 3233.14 3346.06 3994.86 4286.2 3778.99 3746.1 3829.36 4086.72 4191.3 4588.16 4281 4269.86 4124.18 3926.9 3618.54 3421.47 3260.96 3133.28 3351.48 3247.36 3386.97 3346.76 3493.21 3423.47 2994.29 3110.49 2931.84 3391.99 3366.61 3826.72 3724.97 3812.52 3536.94 3514.61 3239.48 3163.78 2890.5 3085.2 3382.47 3651.91 3360.89 3841.11 3755.1 4256.09 4305.76 3876.08 3902.03 3803.24 3560.29 3658.98 3224.36 3622.22 3892.75 4006.81 3686.39 3250.69 3211.31 2933.85 3102.29 2812.49 2810.66 3055.41 3315.57 3399.63 3739.96 3325.69 3963.56 4140.73 4542.34 4898.21 4764.42 4444.56 4622.21 5005.82 5205.29 5446.98 5001.28 4657.55 4433.61 4748.77 4279.86 4477.31 4090.38 3711.02 3997.99 3972.12 4326.72 4247.04 3604.38 3519.16 3631.91 3456.78 3329.28 3244.95 2811.6 2989.35 3287.56 3262.33 3311.03 3562.31 3469.35 3338.16 3125.73 3244.7 2987.65 3181.23 2991.36 2949.32 3228.82 3377.28 3250.38 3283.66 3048.72 2959.79 3180.75 3607.13 3792.61 4244.73 4453.24 4906.87 5044.82 5838.96 5695.67 5667.51 5590.6 5655.09 4759.62 4795.46 5170.32 5192.08 5583.61 5672.27 6234.29 6602.69 6555.94 6713.86 6492.82 6154.44 6715.11 7193.85 7635.42 7805.43 8634.48 7892.32 8788.81 9397.93 9919.89 10370.24 11279.96 12042.56 10398.61 10609.25 10743.88 11699.05 12454.42 12961.9 13696.31 13786.91 14090.92 12938.09 13072.1 13872.37 14544.46 14650.51 15550.99 15318.6 17291.1 19837.99 19363.19 20286.99 17648.71 17578.72 15644.44 17287.31 16415.57 13461.6 14355.75 14564.53 12860.43 9788.06 9092.72 9647.31 9424.24 8891.61 9708.5 11403.25 14625.25 14493.84 15670.31 15666.64 17126.84 15896.28 16926.22 17464.81 16357.96 16429.55 17527.77 17558.71 16944.63 17700.9 17868.29 17971.12 20069.12 20032.34 19521.25 20509.09 18327.76 17823.4 19445.22 19135.96 18503.28 18845.87 18197.2 16676.75 16453.76 17705.01 16123.46 15454.92
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)
0
0
1
2
Degree (D) of seasonal differencing (X series)
0
0
1
2
Seasonal Period
1
1
2
3
4
12
Box-Cox transformation parameter (Y 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 (Y series)
0
0
1
2
Degree (D) of seasonal differencing (Y series)
0
0
1
2
Number of non-seasonal time lags in test
1
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation