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Paper statistiek: stationair maken tijdreeks bakmeel

*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: Sun, 29 Nov 2009 06:57:08 -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/29/t1259503144lbw6acrnv8c09ko.htm/, Retrieved Sun, 29 Nov 2009 14:59:06 +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/29/t1259503144lbw6acrnv8c09ko.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:
ETSHWP(12)
 
Dataseries X:
» Textbox « » Textfile « » CSV «
0.51 0.51 0.51 0.51 0.52 0.52 0.52 0.53 0.53 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.53 0.53 0.53 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.53 0.53 0.53 0.53 0.53 0.54 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.56 0.56 0.56 0.56 0.56 0.55 0.56 0.55 0.55 0.56 0.55 0.55 0.55 0.55
 
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
10.8087345.60311e-06
20.5820584.03269.8e-05
30.3358312.32670.012124
40.0896040.62080.268836
5-0.068094-0.47180.319613
6-0.206243-1.42890.079755
7-0.291275-2.0180.024599
8-0.342739-2.37460.010808
9-0.480888-3.33170.000834
10-0.60502-4.19175.9e-05
11-0.626606-4.34133.6e-05
12-0.59692-4.13567.1e-05
13-0.443294-3.07120.001753
14-0.218846-1.51620.068012
150.0074470.05160.479534
160.1983281.37410.087904
170.3025252.0960.020692
180.33592.32720.01211
190.3338642.31310.012525
200.298262.06640.022104
210.2822071.95520.028199
220.319272.2120.015881
230.28922.00360.025386
240.2255631.56270.062341
250.1265140.87650.192558
26-0.00979-0.06780.473102
27-0.132078-0.91510.182367
28-0.254365-1.76230.042193
29-0.289968-2.0090.025092
30-0.256594-1.77770.040892
31-0.205513-1.42380.080481
32-0.154433-1.06990.144999
33-0.087491-0.60620.273634
34-0.05596-0.38770.349974
35-0.04398-0.30470.380956
36-0.031999-0.22170.412745
370.0153930.10660.457758
380.0646290.44780.32817
390.0821420.56910.285972
400.0856390.59330.277875
410.0695850.48210.315963
420.0553760.38370.351463
430.0234620.16250.435779
44-0.010298-0.07130.47171
45-0.008645-0.05990.476243
46-0.006993-0.04840.480779
47-0.003497-0.02420.490387
48NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8087345.60311e-06
2-0.208105-1.44180.077926
3-0.195061-1.35140.091447
4-0.178815-1.23890.110709
50.060820.42140.337683
6-0.152254-1.05480.148388
7-0.052898-0.36650.357805
8-0.101502-0.70320.242656
9-0.439624-3.04580.001881
10-0.27978-1.93840.029235
110.0640050.44340.329721
12-0.09985-0.69180.246205
130.0475940.32970.371516
140.1291530.89480.18768
15-0.002736-0.0190.492478
16-0.140206-0.97140.168116
170.0171090.11850.45307
18-0.028227-0.19560.422889
19-0.16626-1.15190.127536
20-0.098678-0.68370.248739
210.0130670.09050.464121
220.10010.69350.245666
23-0.144901-1.00390.16023
240.0335360.23230.408629
250.0756530.52410.301297
26-0.032587-0.22580.41117
27-0.006796-0.04710.481321
28-0.04102-0.28420.388742
290.0447460.310.378948
30-0.101039-0.70.243648
310.047130.32650.372722
320.0272180.18860.425611
330.0612320.42420.336648
34-0.015347-0.10630.457884
35-0.017736-0.12290.451359
36-0.004338-0.03010.488073
370.044280.30680.380169
38-0.109482-0.75850.225927
39-0.125739-0.87110.194006
40-0.071-0.49190.312514
41-0.068318-0.47330.319064
420.087420.60570.273797
430.100310.6950.245213
44-0.100558-0.69670.244679
450.0110160.07630.469739
460.0141690.09820.461104
47-0.03768-0.26110.397584
48NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503144lbw6acrnv8c09ko/1xk9m1259503026.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503144lbw6acrnv8c09ko/1xk9m1259503026.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503144lbw6acrnv8c09ko/2lqh21259503026.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503144lbw6acrnv8c09ko/2lqh21259503026.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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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