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Data X:
101.30 97.60 96.40 97.00 96.40 94.70 89.30 85.90 83.30 81.50 85.00 84.80 87.50 89.00 90.00 89.60 87.40 84.80 81.90 81.10 79.10 80.50 88.50 90.90 84.90 80.00 76.50 75.40 73.50 74.30 77.70 77.90 76.70 77.20 86.00 86.90 92.00 101.70 104.50 101.70 100.60 100.30 102.50 101.00 108.60 103.40 106.40 106.60 108.90 110.50 114.00 112.80 109.60 116.00 124.60 129.00 131.50 138.60 138.10 146.30 157.60 158.40 176.30 199.90 210.40 202.60 207.10 202.00 203.40 216.30 207.30 203.50 204.40 203.70 205.70 208.00 209.30 208.70 206.50 204.50
Data Y:
100.70 97.90 96.50 96.60 96.60 95.50 91.80 89.30 87.00 85.90 88.00 87.90 89.20 90.90 91.60 90.20 89.10 87.50 86.30 86.00 84.40 86.10 91.00 92.70 88.00 84.30 82.20 80.80 79.40 80.20 82.20 82.20 81.20 82.10 88.10 88.50 92.10 98.60 100.90 100.60 101.10 102.10 103.60 102.80 108.30 104.00 106.10 106.30 109.00 111.00 113.70 112.70 110.30 114.50 119.30 121.80 125.40 129.70 129.40 134.50 141.20 141.40 152.20 167.70 173.30 168.70 172.60 169.80 172.00 179.40 174.60 172.50 172.60 176.30 178.90 179.60 179.90 180.30 180.90 177.70
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) x <- diff(y,lag=par4,difference=par7) x y bitmap(file='test1.png') (r <- ccf(x,y,main='Cross Correlation Function',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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R Server
Big Analytics Cloud Computing Center
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