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Data X:
0.95 0.98 1.23 1.17 0.84 0.74 0.65 0.91 1.19 1.30 1.53 1.94 1.79 1.95 2.26 2.04 2.16 2.75 2.79 2.88 3.36 2.97 3.10 2.49 2.20 2.25 2.09 2.79 3.14 2.93 2.65 2.67 2.26 2.35 2.13 2.18 2.90 2.63 2.67 1.81 1.33 0.88 1.28 1.26 1.26 1.29 1.10 1.37 1.21 1.74 1.76 1.48 1.04 1.62 1.49 1.79 1.8 1.58 1.86 1.74 1.59 1.26 1.13 1.92 2.61 2.26 2.41 2.26 2.03 2.86 2.55 2.27 2.26 2.57 3.07 2.76 2.51 2.87 3.14 3.11 3.16 2.47 2.57 2.89 2.63 2.38 1.69 1.96 2.19 1.87 1.6 1.63 1.22 1.21 1.49 1.64 1.66 1.77 1.82 1.78 1.28 1.29 1.37 1.12 1.51 2.24 2.94 3.09 3.46 3.64 4.39 4.15 5.21 5.80 5.91
Data Y:
13.92 13.22 13.31 12.91 13.19 12.92 13.43 13.72 13.97 14.91 14.46 14.12 14.23 15.04 14.80 14.49 15.14 14.34 15.12 15.14 14.34 14.36 14.91 15.56 16.50 15.57 15.14 15.19 15.07 14.48 14.27 14.72 14.65 14.38 13.95 14.85 14.87 14.83 15.03 15.47 16.21 16.55 17.04 17.22 17.47 17.75 17.84 18.47 18.38 18.55 18.39 18.88 20.21 19.67 20.09 18.78 19.74 20.64 20.34 21.75 22.10 22.81 22.91 22.46 21.78 25.05 23.70 23.02 24.34 24.15 25.85 26.42 26.54 26.36 26.99 27.52 26.63 26.26 24.86 26.84 26.57 24.67 27.24 27.77 27.61 27.27 28.46 26.97 29.95 29.88 29.67 31.19 30.24 30.03 31.02 30.45 31.70 32.10 32.32 32.18 33.43 33.07 35.32 35.17 35.29 37.89 38.32 37.07 39.77 39.20 40.46 44.95 41.69 41.88 45.86
Sample Range:
(leave blank to include all observations)
From:
To:
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
12
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
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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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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