Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
2648.9 2669.6 3042.3 2604.2 2732.1 2621.7 2483.7 2479.3 2684.6 2834.7 2566.1 2251.2 2350 2299.8 2542.8 2530.2 2508.1 2616.8 2534.1 2181.8 2578.9 2841.9 2529.9 2103.2 2326.2 2452.6 2782.1 2727.3 2648.2 2760.7 2613 2225.4 2713.9 2923.3 2707 2473.9 2521 2531.8 3068.8 2826.9 2674.2 2966.6 2798.8 2629.6 3124.6 3115.7 3083 2863.9 2728.7 2789.4 3225.7 3148.2 2836.5 3153.5 2656.9 2834.7 3172.5 2998.8 3103.1 2735.6 2818.1 2874.4 3438.5 2949.1 3306.8 3530 3003.8 3206.4 3514.6 3522.6 3525.5 2996.2 3231.1 3030 3541.7 3113.2 3390.8 3424.2 3079.8 3123.4 3317.1 3579.9 3317.9 2668.1
Data Y:
99.5 93.5 104.6 95.3 102.8 103.3 100.2 107.9 107.5 119.8 112 102.1 105.3 101.3 108.4 107.4 109.1 109.5 111.4 110.1 117 129.6 113.5 113.3 110.1 107.4 110.1 112.5 106 117.6 117.8 113.5 121.2 130.4 115.2 117.9 110.7 107.6 124.3 115.1 112.5 127.9 117.4 119.3 130.4 126 125.4 130.5 115.9 108.7 124 119.4 118.6 131.3 111.1 124.8 132.3 126.7 131.7 130.9 122.1 113.2 133.6 119.2 129.4 131.4 117.1 130.5 132.3 140.8 137.5 128.6 126.7 120.8 139.3 128.6 131.3 136.3 128.8 133.2 136.3 151.1 145 134.4
Sample Range:
(leave blank to include all observations)
From:
To:
Box-Cox transformation parameter (X series)
0.0
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)
1
0
1
2
Degree (D) of seasonal differencing (X series)
1
0
1
2
Seasonal Period
12
1
2
3
4
12
Box-Cox transformation parameter (Y series)
0.0
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)
1
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation