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Data X:
54.64 52.39 52.51 52.92 55.22 55.41 57.02 58.55 57.49 55.52 57.84 58.69 59.74 60.7 60.74 64.32 66.9 70.93 75.89 80.6 81.39 81.33 77.04 79.54 81.93 80.79 81.98 85.94 86.6 87.42 93.14 95.76 99.75 97.71 94.99 96.41 96.28 100.14 99.9 102.87 107.37 115.68 124.33 128.44 130.19 148.4 169.14 153.98 163.13 165.4 166.35 173.73 174.23 177.04 170.78 174.01 183.76 201.95 205.38 197.36 196.53 179.94 174.84 179.86 172.77 162.56 178.4 190.83 201.07 198.95 190.46 186.27 187.96 174.99 164.1 131.48 116.14 103.43 96.87 93.68 96.49 105.22 110.11 118.47 122.15 137.35 134.83 138.34 141.98 149.45 154.68 145.98 156.33 176.28 159.08 151.18 162.63 174.2 180.51 185.31 186.33
Data Y:
14.36 14.62 13.51 14.95 16.72 16.33 15.21 16.69 15.81 16.02 16.7 15.99 17.68 18.89 18.72 21.14 20.97 23.75 23.05 23.45 21.74 19.37 21.1 21.2 22.67 22.24 23.78 23.27 25.74 26.1 27.49 31.41 28.79 26.76 26.41 27.05 29.43 32.1 36.84 34.22 36.53 40.99 45.97 43.6 47.84 51.47 51.31 48.47 48.28 46.56 43.83 51.17 49.59 49.11 49.97 50.07 53.3 57.08 68.54 71.62 67.64 64.79 80.97 88.42 110.22 99 95.95 107.94 97.82 111.64 114.73 117.58 99.19 90.19 59.74 44.51 23.94 21.29 20.77 25.07 32.95 40.05 44.59 40.28 41.19 38.14 41.85 43.76 50.16 52.94 47.69 51.52 58.69 50.44 45.72 43.24 51.49 50.43 58.73 65.12 64.13
Sample Range:
(leave blank to include all observations)
From:
To:
Box-Cox transformation parameter (X series)
12
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
1
2
Degree (D) of seasonal differencing (X series)
0
1
2
Seasonal Period
1
2
3
4
12
Box-Cox transformation parameter (Y series)
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
1
2
Degree (D) of seasonal differencing (Y series)
0
1
2
Treatment of missing data
(?)
na.fail
na.pass
Chart options
Label y-axis:
Label x-axis:
R Code
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) 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 bitmap(file='test1.png') (r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)')) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Cross Correlation Function',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE) a<-table.element(a,par1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE) a<-table.element(a,par2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE) a<-table.element(a,par3) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Seasonal Period (s)',header=TRUE) a<-table.element(a,par4) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE) a<-table.element(a,par5) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE) a<-table.element(a,par6) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE) a<-table.element(a,par7) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'k',header=TRUE) a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE) a<-table.row.end(a) mylength <- length(r$acf) myhalf <- floor((mylength-1)/2) for (i in 1:mylength) { a<-table.row.start(a) a<-table.element(a,i-myhalf-1,header=TRUE) a<-table.element(a,r$acf[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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