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Data:
18.09 18.13 18 17.72 17.62 17.13 17.39 17.09 17.14 17.38 16.8 16.51 16.01 15.05 13.56 15.22 14.91 15.13 15.25 14.61 14.87 15.1 15.22 15.46 14.96 14 14.2 13.9 13.63 13.32 13.8 14.5 14.12 13.88 14.11 14.26 14.71 14.52 14.32 14.69 15.25 15.04 14.82 14.5 14.72 14.6 14.58 14 14.75 14.41 15.19 14.96 14.83 14.25 14.32 14.93 14.65 15.65 15.65 15.61 15.95 15.83 15.77 16.7 16.69 16.4 16.77 16.78 16.84 16.68 16.67 16.3 16.37 16.6 16.72 16.82 17.5 17.2 17.29 17.2 17.2 17.32 17.16 17.41 17.31 17.3 17.34 17.19 17.05 17.07 17.07 16.81 16.81 16.96 17.05 17 16.77 16.66 16.2 16.26 15.84 15.85 15.71 15.84 15.73 15.77 15.3 15.41 15.4 15.61 15 14.12 14.01 13.46 13.85 13.92 13.59 13.67 13.05 12.87 12.28 11.88 12.49 11.9 10.8 10.99 10.15 10.07 10.05 10.31 9.94 9.65 9.74 9.85 9.96 9.63 9.43 8.77 9.53 9.5 9.78 9.9 9.93 10.35 9.79 9.63 9.02 9.25 9.11 8.95 9.3 9.13 9.75 9.65 9.27 9.59 9.58 9.98 9.57 9.6 9.64 9.46 9.19 9.02 8.9 9.12 8.86 8.94 9 9.23 9.39 9.62 9.9 9.8 9.2 9.87 9.6 9.37 9.21 9.15 8.7 8.2 8.1 6.68 7.7 8.2 7.55 7.53 7.02 6.6 6 3.95 4.91 5.15 5.7 1.93 1.36 1.1 0.98 1 1.1 1.06 1.01 0.93 0.89 0.9 0.88 0.85 0.84 0.94 1 1.1 1.15 1.05 1.06 0.99 0.93 0.84 0.9 0.86 0.78 0.77 0.6 0.57 0.62 0.62 0.58 0.6 0.73 0.75 0.63 0.71 0.68 0.64 0.66 0.69 0.72 0.92 0.85 0.95 1 1.15 1.07 1.01 0.99 0.95 0.92 0.94 0.96 1.05 1.04 1.1 1.14 1.12 1.19 1.35 1.62 1.43 1.45 1.47 1.35 1.15 1.46 1.3 1.3 1.5 1.52 1.63 1.9 1.65 1.5 1.38 1.39
Sample Range:
(leave blank to include all observations)
From:
To:
Number of time lags
48
Default
5
6
7
8
9
10
11
12
24
36
48
60
Box-Cox transformation parameter (Lambda)
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 of non-seasonal differencing (d)
0
0
1
2
Degree of seasonal differencing (D)
0
0
1
2
Seasonality
12
12
1
2
3
4
6
12
CI type
White Noise
MA
Confidence Interval
Use logarithms with this base
(overrules the Box-Cox lambda parameter)
(?)
Chart options
R Code
if (par1 == 'Default') { par1 = 10*log10(length(x)) } else { par1 <- as.numeric(par1) } par2 <- as.numeric(par2) par3 <- as.numeric(par3) par4 <- as.numeric(par4) par5 <- as.numeric(par5) if (par2 == 0) { x <- log(x) } else { x <- (x ^ par2 - 1) / par2 } if (par3 > 0) x <- diff(x,lag=1,difference=par3) if (par4 > 0) x <- diff(x,lag=par5,difference=par4) bitmap(file='pic1.png') racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF') dev.off() bitmap(file='pic2.png') rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') dev.off() (myacf <- c(racf$acf)) (mypacf <- c(rpacf$acf)) lengthx <- length(x) sqrtn <- sqrt(lengthx) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Autocorrelation Function',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Time lag k',header=TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,'P-value',header=TRUE) a<-table.row.end(a) for (i in 2:(par1+1)) { a<-table.row.start(a) a<-table.element(a,i-1,header=TRUE) a<-table.element(a,round(myacf[i],6)) mytstat <- myacf[i]*sqrtn a<-table.element(a,round(mytstat,4)) a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Partial Autocorrelation Function',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Time lag k',header=TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,'P-value',header=TRUE) a<-table.row.end(a) for (i in 1:par1) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,round(mypacf[i],6)) mytstat <- mypacf[i]*sqrtn a<-table.element(a,round(mytstat,4)) a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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