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Data:
46 62 66 59 58 61 41 27 58 70 49 59 44 36 72 45 56 54 53 35 61 52 47 51 52 63 74 45 51 64 36 30 55 64 39 40 63 45 59 55 40 64 27 28 45 57 45 69 60 56 58 50 51 53 37 22 55 70 62 58 39 49 58 47 42 62 39 40 72 70 54 65
Sample Range:
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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
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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R Server
Big Analytics Cloud Computing Center
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