Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
105.3 103 103.8 103.4 105.8 101.4 97 94.3 96.6 97.1 95.7 96.9 97.4 95.3 93.6 91.5 93.1 91.7 94.3 93.9 90.9 88.3 91.3 91.7 92.4 92 95.6 95.8 96.4 99 107 109.7 116.2 115.9 113.8 112.6 113.7 115.9 110.3 111.3 113.4 108.2 104.8 106 110.9 115 118.4 121.4 128.8 131.7 141.7 142.9 139.4 134.7 125 113.6 111.5 108.5 112.3 116.6 115.5 120.1 132.9 128.1 129.3 132.5 131 124.9 120.8 122 122.1 127.4 135.2 137.3 135 136 138.4 134.7 138.4 133.9 133.6 141.2 151.8 155.4 156.6 161.6 160.7 156 159.5 168.7 169.9 169.9 185.9 190.8 195.8 211.9
Data Y:
103.1 102.5 101.3 99.5 99.4 98.8 99.9 99.9 101.2 97.7 97 99.5 100.3 98.5 95.1 93.1 92.2 89 86.4 84.5 82.7 80.8 81.8 81.8 82.9 83.8 86.2 86.1 86.2 88.8 89.6 87.8 88.3 88.6 91 91.5 95.4 98.7 99.9 98.6 100.3 100.2 100.4 101.4 103 109.1 111.4 114.1 121.8 127.6 129.9 128 123.5 124 127.4 127.6 128.4 131.4 135.1 134 144.5 147.3 150.9 148.7 141.4 138.9 139.8 145.6 147.9 148.5 151.1 157.5 167.5 172.3 173.5 187.5 205.5 195.1 204.5 204.5 201.7 207 206.6 210.6 211.1 215 223.9 238.2 238.9 229.6 232.2 222.1 221.6 227.3 221 213.6
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')
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