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Data:
102.8 106.3 103.7 106.9 104.3 105.4 96.2 95.7 95.9 93.6 94.7 94.5 96.6 96.7 98.9 102 105.2 106.4 99.3 96.4 93.1 95.6 93.3 96.7 105.6 105.2 107 104.9 104.5 105.2 99.7 100.2 98.5 98.4 97.1 98.4 100.6 111.3 119 117.8 108.8 109.3 103.5 103.7 110 105.5 110.4 106.7 110.2 105.2 108 108.1 107.2 106 99.4 100.2 100.3 100.8 99.5 100.2 103 111 120.5 109.5 106.6 105.5 103.9 104.9 104.8 99.6 97 95.4 99.3 103.9 107.4 107.4 111 113.2 108.5 113.3 113.8 105.3 107.5 109.4 118.9 119 115 124.1 120.5 117.7 117.1 118.1 119.6 118.8 124.9 124 124.9 121.7 121.6 125.1 127.9 129 130.1 130.3 127.9 124.1 125.7 129.2 129.2 132.6 131.5 131 125.8 127.2 127.3 127.5 122 118.4 118.3 115.5
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)
1
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
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 #par6 == 'White Noise'# par6 <- 'white' else par6 <- 'ma' par7 <- as#numeric#par7# 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='time lag', ylab='ACF', ci#type=par6, ci=par7, sub=paste#'#lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,'#',sep=''## dev#off## bitmap#file='pic2#png'# rpacf <- pacf#x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF'# dev#off## 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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Big Analytics Cloud Computing Center
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