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Paper DMA ACF, PACF Olie

*The author of this computation has been verified*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Wed, 15 Dec 2010 19:15:31 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf.htm/, Retrieved Wed, 15 Dec 2010 20:17:02 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
25,64 27,97 27,62 23,31 29,07 29,58 28,63 29,92 32,68 31,54 32,43 26,54 25,85 27,6 25,71 25,38 28,57 27,64 25,36 25,9 26,29 21,74 19,2 19,32 19,82 20,36 24,31 25,97 25,61 24,67 25,59 26,09 28,37 27,34 24,46 27,46 30,23 32,33 29,87 24,87 25,48 27,28 28,24 29,58 26,95 29,08 28,76 29,59 30,7 30,52 32,67 33,19 37,13 35,54 37,75 41,84 42,94 49,14 44,61 40,22 44,23 45,85 53,38 53,26 51,8 55,3 57,81 63,96 63,77 59,15 56,12 57,42 63,52 61,71 63,01 68,18 72,03 69,75 74,41 74,33 64,24 60,03 59,44 62,5 55,04 58,34 61,92 67,65 67,68 70,3 75,26 71,44 76,36 81,71 92,6 90,6 92,23 94,09 102,79 109,65 124,05 132,69 135,81 116,07 101,42 75,73 55,48 43,8 45,29
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1508421.56760.059951
2-0.086445-0.89840.185496
30.0377580.39240.347769
4-0.02056-0.21370.415606
5-0.020744-0.21560.414862
6-0.022369-0.23250.408308
7-0.072594-0.75440.226119
8-0.067451-0.7010.242414
9-0.007935-0.08250.467217
100.1152311.19750.116863
110.0900290.93560.17578
120.0282740.29380.384724
13-0.210385-2.18640.015473
14-0.142509-1.4810.070759
150.0358510.37260.355097
16-0.018899-0.19640.42233
17-0.072717-0.75570.225737
18-0.062022-0.64450.260294
190.0693970.72120.236175
200.0208160.21630.414569
21-0.036692-0.38130.351861
220.1222261.27020.10337
23-0.057225-0.59470.276645
24-0.029739-0.30910.378935
250.157251.63420.052565
260.0612760.63680.262801
270.0233130.24230.404512
280.0059830.06220.47527
29-0.063545-0.66040.25521
300.0021010.02180.49131
310.0461140.47920.316373
32-0.048158-0.50050.308881
33-0.066276-0.68880.246227
34-0.102685-1.06710.144146
350.0089510.0930.463029
360.1129551.17390.121517
370.0687170.71410.238344
38-0.016674-0.17330.431376
39-0.068657-0.71350.238538
40-0.054361-0.56490.286645
410.0321010.33360.369664
420.0129340.13440.446661
43-0.092763-0.9640.168594
44-0.054615-0.56760.285749
45-0.063917-0.66420.253974
460.0166110.17260.431634
470.0724090.75250.226696
480.0574530.59710.275857
49-0.057843-0.60110.274509
50-0.031438-0.32670.37226
51-0.058782-0.61090.271282
52-0.010503-0.10920.456642
53-0.016779-0.17440.430951
54-0.155265-1.61360.05477
55-0.077901-0.80960.209982
560.0107690.11190.455549
57-0.032327-0.3360.368778
580.026240.27270.392804
590.0505480.52530.300222
60-0.014694-0.15270.439457


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1508421.56760.059951
2-0.11174-1.16120.124052
30.0716130.74420.229178
4-0.050718-0.52710.299612
50.0025730.02670.489359
6-0.030481-0.31680.376015
7-0.065038-0.67590.250278
8-0.051078-0.53080.298316
9-0.001242-0.01290.494864
100.1155171.20050.116288
110.0550030.57160.284388
120.0260410.27060.393599
13-0.236975-2.46270.007685
14-0.082663-0.85910.196104
150.0237160.24650.402894
16-0.014358-0.14920.440832
17-0.039318-0.40860.34182
18-0.049717-0.51670.303222
190.0919650.95570.170672
20-0.054295-0.56420.286878
21-0.073443-0.76320.223493
220.1049141.09030.139005
23-0.067628-0.70280.241842
240.0731190.75990.224492
250.1515851.57530.059053
26-0.00465-0.04830.480774
270.0053440.05550.477907
28-0.000924-0.00960.496177
29-0.070704-0.73480.232033
30-0.001594-0.01660.493408
310.0242610.25210.40071
32-0.023803-0.24740.402545
33-0.010092-0.10490.458334
34-0.1661-1.72620.043589
350.0602380.6260.266312
360.0771610.80190.212191
370.0196290.2040.419372
380.0506340.52620.299911
39-0.037495-0.38970.348777
40-0.033199-0.3450.365376
410.017120.17790.429561
42-0.000573-0.0060.49763
43-0.056228-0.58430.280105
44-0.010578-0.10990.456334
45-0.06396-0.66470.253831
460.0169150.17580.430397
47-0.078785-0.81880.207363
480.0577990.60070.274661
49-0.026227-0.27260.392858
50-0.038622-0.40140.344468
51-0.069654-0.72390.235355
52-0.020422-0.21220.416163
53-0.033421-0.34730.364512
54-0.116194-1.20750.114934
55-0.034765-0.36130.359295
56-0.008681-0.09020.46414
57-0.069559-0.72290.235659
58-0.01319-0.13710.445615
590.0756130.78580.216855
60-0.065031-0.67580.250299
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/1x2jl1292440526.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/1x2jl1292440526.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/28bio1292440526.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/28bio1292440526.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/3ikh91292440526.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/15/t12924406213ct7bnsufijuwaf/3ikh91292440526.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = -0.5 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = -0.5 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
R code (references can be found in the software module):
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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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