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tijdreeks bevolkingstotaal

*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, 26 Dec 2010 10:33:29 +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/26/t1293359489nw8dkkwkhoit8fu.htm/, Retrieved Sun, 26 Dec 2010 11:31:30 +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/26/t1293359489nw8dkkwkhoit8fu.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 «
5140 4749 3635 4305 5805 4260 3869 7325 9280 6222 3272 7598 1345 1900 1480 1472 3823 4454 3357 5393 8329 4152 4042 7747 1451 911 -406 1387 2150 1577 2642 4273 8064 3243 1112 2280 505 744 -1369 -531 1041 2076 577 5080 6584 3761 294 5020 1141 3805 2127 2531 3682 3263 2798 5936 10568 5296 1870 4390 3707 5201 3748 5282 5349 6249 5517 8640 15767 8850 5582 6496 3255 6189 6452 5099 6833 7046 7739 10142 16054 7721 6182 6490 3704 6235 4655 5072 3640 5147 5703 11889 15603 9589
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5975475.79340
20.3430893.32640.000628
30.2786792.70190.00409
40.165811.60760.055639
50.0938710.91010.182545
60.0712760.69110.245619
70.0863460.83720.202315
80.1203461.16680.123122
90.2430892.35680.010253
100.2360272.28840.012178
110.437934.24592.6e-05
120.7131966.91470
130.425524.12564e-05
140.2103082.0390.022129
150.1568841.5210.065803
160.0655910.63590.263184
17-0.018499-0.17940.429022
18-0.065457-0.63460.263605
19-0.053654-0.52020.302075
20-0.026818-0.260.397712
210.0576870.55930.288645
220.0436480.42320.336565
230.1987691.92710.028491
240.4093763.9697.1e-05
250.1567751.520.065935
26-0.031106-0.30160.381818
27-0.073484-0.71250.238975
28-0.1319-1.27880.102055
29-0.194203-1.88290.031405
30-0.234196-2.27060.012727
31-0.221322-2.14580.017232
32-0.172545-1.67290.048837
33-0.086909-0.84260.200791
34-0.138838-1.34610.090756
35-0.036729-0.35610.361281
360.1489441.44410.076023
37-0.038602-0.37430.354528
38-0.175386-1.70040.046178
39-0.209423-2.03040.022569
40-0.235504-2.28330.012333
41-0.290379-2.81530.002968
42-0.300339-2.91190.002243
43-0.272209-2.63920.004865
44-0.205881-1.99610.024409
45-0.098968-0.95950.169877
46-0.121373-1.17680.121131
47-0.057523-0.55770.289185
480.0857750.83160.203867


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5975475.79340
2-0.021734-0.21070.416783
30.1279081.24010.10901
4-0.07481-0.72530.235031
50.0088590.08590.465869
60.0069350.06720.473268
70.0632820.61350.270499
80.0682280.66150.254958
90.2123232.05860.021152
10-0.026577-0.25770.398612
110.4362144.22922.7e-05
120.4819634.67285e-06
13-0.406655-3.94277.8e-05
14-0.10552-1.02310.154455
15-0.017018-0.1650.434652
16-0.088783-0.86080.195775
17-0.043125-0.41810.338409
18-0.165848-1.6080.0556
190.0038170.0370.485278
20-0.060187-0.58350.280464
21-0.143849-1.39470.083202
220.0250390.24280.404361
23-0.063572-0.61640.269576
24-0.000922-0.00890.496442
25-0.194072-1.88160.031492
26-0.096492-0.93550.175957
27-0.009427-0.09140.463685
28-0.076067-0.73750.231329
290.013690.13270.447346
30-0.020778-0.20150.420391
31-0.052649-0.51050.305464
320.0868720.84230.200892
33-0.004497-0.04360.482659
34-0.09164-0.88850.188276
35-0.078188-0.75810.225155
360.0548990.53230.297898
370.0493630.47860.31667
380.0288340.27960.390215
39-0.038019-0.36860.356623
400.056540.54820.292436
41-0.033813-0.32780.371887
420.0651750.63190.264495
430.0324880.3150.376737
440.0304610.29530.384195
450.0887070.860.195977
460.1412121.36910.087114
47-0.026806-0.25990.397758
480.0357810.34690.364719
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/1olu71293359606.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/1olu71293359606.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/2ycta1293359606.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/2ycta1293359606.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/3ycta1293359606.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/26/t1293359489nw8dkkwkhoit8fu/3ycta1293359606.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 48 ; 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 (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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Software written by Ed van Stee & Patrick Wessa


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