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Uitvoer EU - (Partial) Autocorrelation D=1

*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: Thu, 04 Dec 2008 10:52:47 -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/04/t1228413563ycv20p764uowk2q.htm/, Retrieved Thu, 04 Dec 2008 17:59:26 +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/04/t1228413563ycv20p764uowk2q.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 «
11178.4 9516.4 12102.8 12989.0 11610.2 10205.5 11356.2 11307.1 12648.6 11947.2 11714.1 12192.5 11268.8 9097.4 12639.8 13040.1 11687.3 11191.7 11391.9 11793.1 13933.2 12778.1 11810.3 13698.4 11956.6 10723.8 13938.9 13979.8 13807.4 12973.9 12509.8 12934.1 14908.3 13772.1 13012.6 14049.9 11816.5 11593.2 14466.2 13615.9 14733.9 13880.7 13527.5 13584.0 16170.2 13260.6 14741.9 15486.5 13154.5 12621.2 15031.6 15452.4 15428 13105.9 14716.8 14180.0 16202.2 14392.4 15140.6 15960.1 14351.3 13230.2 15202.1 17157.3 16159.1 13405.7 17224.7 17338.4 17370.6 18817.8 16593.2 17979.5 17015.2
 
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
1-0.558045-4.32263e-05
2-0.084385-0.65360.25792
30.3560772.75820.003846
4-0.206466-1.59930.057506
5-0.102017-0.79020.216256
60.2978972.30750.012246
7-0.248107-1.92180.02969
8-0.005706-0.04420.482446
90.2184491.69210.047908
10-0.160803-1.24560.108881
11-0.060119-0.46570.321565
120.1608731.24610.108783
13-0.13625-1.05540.147739
140.0169410.13120.448019
150.1231970.95430.171885
16-0.231088-1.790.03925
170.1432961.110.135721
180.0494390.3830.351553
19-0.135881-1.05250.148389
200.1127920.87370.192887
210.0222180.17210.431969
22-0.20345-1.57590.060152
230.3593812.78380.003588
24-0.311442-2.41240.00946
250.0394010.30520.380635
260.1459271.13030.131415
27-0.050544-0.39150.348402
28-0.121779-0.94330.174656
290.1896791.46920.073495
30-0.155182-1.2020.117037
31-0.000373-0.00290.498853
320.1455181.12720.132078
33-0.185886-1.43990.077551
340.0588330.45570.32512
350.0869230.67330.251671
36-0.140352-1.08720.140656
370.0483550.37460.354657
380.0595710.46140.323077
39-0.11332-0.87780.191783
400.0826990.64060.262117
410.0404790.31360.377474
42-0.122904-0.9520.172455
430.0826350.64010.262276
440.0583740.45220.326392
45-0.184301-1.42760.079298
460.1902371.47360.072912
47-0.07656-0.5930.277695
48-0.054256-0.42030.337897
490.1002450.77650.220254
50-0.009935-0.0770.469457
51-0.102455-0.79360.215274
520.121010.93730.17617
53-0.036129-0.27990.390276
54-0.057398-0.44460.329102
550.0888070.68790.247085
56-0.06938-0.53740.296486
570.0263030.20370.419623
580.0037450.0290.488476
59-0.004787-0.03710.485273
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.558045-4.32263e-05
2-0.574801-4.45241.9e-05
3-0.08425-0.65260.258254
40.0479120.37110.355927
5-0.107897-0.83580.203302
60.1088760.84330.201192
7-0.013951-0.10810.457152
8-0.105193-0.81480.209199
90.0195960.15180.439931
100.1054970.81720.208531
11-0.00839-0.0650.4742
12-0.079644-0.61690.269812
13-0.130032-1.00720.158936
14-0.075307-0.58330.280931
150.0545620.42260.337037
16-0.163496-1.26640.105127
17-0.102348-0.79280.215513
18-0.049175-0.38090.352309
190.0082440.06390.474647
200.1171910.90780.183819
210.1520451.17770.121776
22-0.114676-0.88830.188971
230.2472711.91540.030109
24-0.055747-0.43180.333713
25-0.045977-0.35610.361495
26-0.130932-1.01420.157282
270.0712720.55210.291474
280.0139910.10840.457031
29-0.022159-0.17160.432148
30-0.107405-0.8320.204367
31-0.100071-0.77510.22065
32-0.036768-0.28480.388387
33-0.124104-0.96130.170128
340.056580.43830.331383
35-0.002805-0.02170.491369
36-0.06661-0.5160.303891
37-0.086464-0.66980.252793
38-0.097929-0.75860.225545
390.023850.18470.427029
40-0.040635-0.31480.37702
410.0094380.07310.470982
42-0.029647-0.22960.409575
430.0179790.13930.444853
440.0442950.34310.366359
45-0.06659-0.51580.303944
46-0.108581-0.84110.201825
47-0.028949-0.22420.411667
48-0.045772-0.35460.362084
49-0.054823-0.42470.336302
50-0.026215-0.20310.419886
510.096290.74590.229331
520.0065490.05070.479854
530.0322580.24990.401771
540.0035140.02720.489188
550.0449820.34840.36437
560.0122830.09510.46226
570.0469460.36360.358702
58-0.001422-0.0110.495623
59-0.00863-0.06680.473462
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t1228413563ycv20p764uowk2q/1i32d1228413165.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t1228413563ycv20p764uowk2q/1i32d1228413165.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t1228413563ycv20p764uowk2q/2q1s31228413165.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t1228413563ycv20p764uowk2q/2q1s31228413165.ps (open in new window)


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