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ws8.2

*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: Fri, 27 Nov 2009 09:33:59 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/27/t1259339754x845ouvnx6flc5g.htm/, Retrieved Fri, 27 Nov 2009 17:35:57 +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/2009/Nov/27/t1259339754x845ouvnx6flc5g.htm/},
    year = {2009},
}
@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 = {2009},
    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 «
2.05 2.11 2.09 2.05 2.08 2.06 2.06 2.08 2.07 2.06 2.07 2.06 2.09 2.07 2.09 2.28 2.33 2.35 2.52 2.63 2.58 2.70 2.81 2.97 3.04 3.28 3.33 3.50 3.56 3.57 3.69 3.82 3.79 3.96 4.06 4.05 4.03 3.94 4.02 3.88 4.02 4.03 4.09 3.99 4.01 4.01 4.19 4.30 4.27 3.82 3.15 2.49 1.81 1.26 1.06 0.84 0.78 0.70 0.36 0.35
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9368247.25660
20.8480056.56860
30.7486095.79870
40.6362744.92863e-06
50.5167234.00258.7e-05
60.3985293.0870.00153
70.28072.17430.016819
80.1767931.36940.087984
90.0911680.70620.241403
100.0255710.19810.42183
11-0.017439-0.13510.446499
12-0.044787-0.34690.364934
13-0.070718-0.54780.292938
14-0.102283-0.79230.215658
15-0.14086-1.09110.139795
16-0.179391-1.38960.084899
17-0.217527-1.6850.048596
18-0.250663-1.94160.028441
19-0.281071-2.17720.016706
20-0.308424-2.3890.010027
21-0.337199-2.61190.005679
22-0.357533-2.76940.003731
23-0.375581-2.90920.002537
24-0.385714-2.98770.002034
25-0.389218-3.01490.001882
26-0.383709-2.97220.002125
27-0.375482-2.90850.002543
28-0.364563-2.82390.003215
29-0.34519-2.67380.004823
30-0.32552-2.52150.00718
31-0.303844-2.35360.010944
32-0.276156-2.13910.018253
33-0.246673-1.91070.030411
34-0.216412-1.67630.04944
35-0.181787-1.40810.082129
36-0.150377-1.16480.124351
37-0.117661-0.91140.182866
38-0.087783-0.680.249571
39-0.05875-0.45510.325349
40-0.033732-0.26130.397384
41-0.004029-0.03120.487604
420.0224110.17360.431386
430.0441410.34190.366806
440.0652390.50530.307585
450.0849640.65810.256486
460.0980860.75980.225183
470.1123680.87040.193776
480.1280710.9920.162582
490.1424751.10360.137085
500.152681.18270.120805
510.1556361.20560.116362
520.1525561.18170.120994
530.1430471.1080.136134
540.127150.98490.164314
550.1094410.84770.19998
560.0899730.69690.244269
570.068820.53310.297974
580.0484920.37560.354263
590.0253270.19620.422566
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9368247.25660
2-0.242198-1.87610.032757
3-0.09841-0.76230.22444
4-0.145466-1.12680.132163
5-0.097164-0.75260.227307
6-0.045864-0.35530.361819
7-0.080316-0.62210.268108
80.0360.27890.390658
90.0347730.26940.394291
100.0469330.36350.358738
110.0617390.47820.317113
12-0.00653-0.05060.479914
13-0.107395-0.83190.204387
14-0.14495-1.12280.133003
15-0.133493-1.0340.152635
16-0.04168-0.32290.373964
17-0.030064-0.23290.408326
180.035330.27370.392642
190.0078860.06110.475749
20-0.002885-0.02230.491122
21-0.081349-0.63010.265503
22-0.022388-0.17340.431455
23-0.119212-0.92340.179746
24-0.054153-0.41950.338187
25-0.056305-0.43610.332152
260.0152290.1180.453246
27-0.011593-0.08980.464373
28-0.006175-0.04780.481006
290.045020.34870.364258
30-0.072167-0.5590.289121
31-0.049554-0.38380.351225
32-0.027999-0.21690.414518
33-0.040692-0.31520.376851
34-0.019534-0.15130.440119
350.0287160.22240.412367
36-0.028496-0.22070.413026
370.030430.23570.407231
38-0.054248-0.42020.337918
39-0.008461-0.06550.473982
40-0.065923-0.51060.305739
410.0366710.28410.388674
42-0.041871-0.32430.373408
43-0.018291-0.14170.443904
440.0125650.09730.461395
45-0.000572-0.00440.498241
46-0.054516-0.42230.337166
470.0132740.10280.459223
480.0016220.01260.495008
49-0.010367-0.08030.468133
50-0.021764-0.16860.433346
51-0.061503-0.47640.31776
52-0.025928-0.20080.420752
53-0.067624-0.52380.301169
54-0.048224-0.37350.355031
55-0.021357-0.16540.434582
56-0.003932-0.03050.487903
57-0.015959-0.12360.451014
580.0151260.11720.453559
59-0.068354-0.52950.299216
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/27/t1259339754x845ouvnx6flc5g/1apjf1259339637.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/27/t1259339754x845ouvnx6flc5g/1apjf1259339637.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/27/t1259339754x845ouvnx6flc5g/278ye1259339637.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/27/t1259339754x845ouvnx6flc5g/278ye1259339637.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; 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 (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()
(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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