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Q3

*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: Mon, 08 Dec 2008 12:17:56 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/08/t1228763920fhnf09vd1wvb4sw.htm/, Retrieved Mon, 08 Dec 2008 19:18:40 +0000
 
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/2008/Dec/08/t1228763920fhnf09vd1wvb4sw.htm/},
    year = {2008},
}
@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 = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:
2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply
test

Post a new message
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
22780 17351 21382 24561 17409 11514 31514 27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698 31956 29506 34506 27165 26736 23691 18157 17328 18205 20995 17382 9367 31124 26551 30651 25859 25100 25778 20418 18688 20424 24776 19814 12738 31566 30111 30019 31934 25826 26835
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2830862.19280.016106
20.3113592.41180.009476
30.0096990.07510.470182
40.0083310.06450.47438
5-0.032884-0.25470.399904
60.0778140.60270.274476
70.0117210.09080.46398
80.1227670.95090.172723
90.056070.43430.33281
10-0.202494-1.56850.06101
11-0.286449-2.21880.015146
12-0.362871-2.81080.003333
13-0.240823-1.86540.033508
14-0.022812-0.17670.43017
150.0201340.1560.438294
160.0406880.31520.376865
170.0751610.58220.281308
180.0225910.1750.430838
19-0.055475-0.42970.334475
20-0.045599-0.35320.362586
210.0780630.60470.273839
22-0.015876-0.1230.451268
230.2694382.08710.02057
240.0302040.2340.407907
250.1781041.37960.086417
260.0435310.33720.368575
270.0457160.35410.362247
28-0.130555-1.01130.157974
290.0316770.24540.403505
30-0.144798-1.12160.13325
31-0.077694-0.60180.274782
32-0.139171-1.0780.142671
33-0.165926-1.28530.10182
34-0.09903-0.76710.223019
35-0.125592-0.97280.167272
36-0.221891-1.71880.045407
37-0.123632-0.95770.171041
38-0.144642-1.12040.133506
39-0.025383-0.19660.422395
40-0.042846-0.33190.370566
41-0.008597-0.06660.473563
420.0405440.31410.377284
430.0657590.50940.306181
440.1041070.80640.211596
450.0198860.1540.439048
460.0756320.58580.280089
470.00920.07130.471713
480.1074150.8320.204344
490.0353180.27360.392678
500.0685120.53070.298796
51-0.053887-0.41740.338935
520.0597740.4630.322517
53-0.02158-0.16720.433905
540.0180290.13960.444702
55-0.019803-0.15340.439302
560.0087710.06790.473031
57-0.01634-0.12660.449851
58-0.000337-0.00260.498964
59-0.002112-0.01640.493501
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2830862.19280.016106
20.2513651.94710.028106
3-0.147892-1.14560.128261
4-0.047743-0.36980.356412
50.0215060.16660.434128
60.1131280.87630.192185
7-0.030411-0.23560.407288
80.0769170.59580.276776
90.0268650.20810.417931
10-0.33251-2.57560.006244
11-0.236957-1.83550.035697
12-0.128185-0.99290.162369
13-0.00198-0.01530.493906
140.1727421.33810.092964
150.0420780.32590.372804
16-0.026132-0.20240.420139
170.049350.38230.351808
180.0758580.58760.279506
19-0.010785-0.08350.466849
20-0.022186-0.17180.432067
210.1444211.11870.133868
22-0.272991-2.11460.019315
230.0653290.5060.307343
24-0.075904-0.58790.279386
250.1145770.88750.189175
260.1212750.93940.175648
270.0133880.10370.458876
28-0.142004-1.10.137872
290.0344970.26720.395111
30-0.089739-0.69510.244832
31-0.16165-1.25210.107689
32-0.135939-1.0530.148286
33-0.024854-0.19250.423994
34-0.030465-0.2360.407124
35-0.056142-0.43490.332607
36-0.093629-0.72520.23556
370.0790940.61270.271209
380.0186380.14440.442848
390.10650.82490.206334
40-0.091242-0.70680.241226
41-0.100949-0.78190.218661
420.0203590.15770.43761
43-0.142667-1.10510.136765
44-0.03674-0.28460.38847
450.0662590.51320.304835
46-0.041173-0.31890.375447
47-0.049812-0.38580.350488
48-0.009552-0.0740.470633
490.0933550.72310.236208
50-0.014186-0.10990.456434
51-0.037209-0.28820.387086
52-0.041241-0.31950.375247
530.0221660.17170.432128
540.0477570.36990.356372
55-0.027669-0.21430.415509
560.0371010.28740.387403
570.0536110.41530.339714
58-0.030971-0.23990.405612
590.0922220.71430.238892
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228763920fhnf09vd1wvb4sw/1yoox1228763871.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228763920fhnf09vd1wvb4sw/1yoox1228763871.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228763920fhnf09vd1wvb4sw/204xp1228763871.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228763920fhnf09vd1wvb4sw/204xp1228763871.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 0.4 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 0.4 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
 
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 (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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