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Paper: autocorrelation werkloosheid 31/01/2002 - 31/12/2007 met d en D = 1 en lambda = 1.9

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Fri, 05 Dec 2008 06:14:10 -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/05/t1228483800utt44bpvwvufltg.htm/, Retrieved Fri, 05 Dec 2008 13:30:02 +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/05/t1228483800utt44bpvwvufltg.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 «
95.20 95.00 94.00 92.20 91.00 91.20 103.40 105.00 104.60 103.80 101.80 102.40 103.80 103.40 102.00 101.80 100.20 101.40 113.80 116.00 115.60 113.00 109.40 111.00 112.40 112.20 111.00 108.80 107.40 108.60 118.80 122.20 122.60 122.20 118.80 119.00 118.20 117.80 116.80 114.60 113.40 113.80 124.20 125.80 125.60 122.40 119.00 119.40 118.60 118.00 116.00 114.80 114.60 114.60 124.00 125.20 124.00 117.60 113.20 111.40 112.20 109.80 106.40 105.20 102.20 99.80 111.00 113.00 108.40 105.40 102.00 102.80
 
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
10.0475790.36550.358038
20.0983050.75510.226597
3-0.054299-0.41710.339068
4-0.051074-0.39230.348121
5-0.072491-0.55680.28988
6-0.059142-0.45430.325648
7-0.012719-0.09770.461251
80.0018390.01410.49439
90.1801531.38380.085819
10-0.158128-1.21460.114677
110.0262030.20130.42059
12-0.269393-2.06920.021456
13-0.088676-0.68110.249226
140.1085190.83350.203948
15-0.008608-0.06610.473752
160.0245590.18860.42551
17-0.100869-0.77480.220779
180.15271.17290.122772
190.065810.50550.307547
200.0761880.58520.280319
210.0132750.1020.459563
220.0131790.10120.459856
230.1399311.07480.143414
24-0.145774-1.11970.133687
25-0.097161-0.74630.229223
26-0.262285-2.01470.024253
270.0418920.32180.37438
28-0.075254-0.5780.28272
290.1146180.88040.191108
30-0.08963-0.68850.24693
31-0.065636-0.50420.308013
320.0388920.29870.383096
33-0.09087-0.6980.243965
34-0.017855-0.13710.44569
35-0.032802-0.2520.400975
360.0503170.38650.350262
370.0939240.72140.236743
380.1345781.03370.152745
39-0.113019-0.86810.194425
40-0.017193-0.13210.447691
41-0.011348-0.08720.465417
42-0.096518-0.74140.230704
430.0471890.36250.359148
44-0.061038-0.46880.320456
45-0.026289-0.20190.420332
460.0222210.17070.432529
47-0.032091-0.24650.403078
48-0.042965-0.330.371276
49-0.080695-0.61980.268879
50-0.04927-0.37840.353228
510.0541090.41560.339597
520.1005080.7720.221592
530.0037990.02920.488409
540.0865770.6650.254316
550.0097130.07460.470389
560.0377770.29020.386351
57-0.002909-0.02230.491125
580.0016470.01270.494974
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0475790.36550.358038
20.096260.73940.231303
3-0.06384-0.49040.312846
4-0.055971-0.42990.33441
5-0.056878-0.43690.331894
6-0.046972-0.36080.359771
7-0.001213-0.00930.496297
80.0032670.02510.490034
90.1731831.33020.094278
10-0.19269-1.48010.072086
110.0041590.03190.487311
12-0.243798-1.87270.033037
13-0.067303-0.5170.303558
140.1935061.48630.071256
15-0.040734-0.31290.377736
16-0.031929-0.24530.403557
17-0.166986-1.28260.102317
180.1344221.03250.153022
190.1629261.25150.107854
200.0097810.07510.470184
210.1142980.87790.191769
22-0.121804-0.93560.176649
230.1251310.96110.1702
24-0.186631-1.43350.078492
25-0.145155-1.1150.134695
26-0.102182-0.78490.217833
270.0038710.02970.48819
28-0.01817-0.13960.444737
290.0007430.00570.497733
30-0.108281-0.83170.20446
310.0075470.0580.476986
320.0035570.02730.489146
330.0267520.20550.418951
34-0.076035-0.5840.280711
350.1172750.90080.185678
36-0.087434-0.67160.252233
37-0.00567-0.04360.482704
38-0.023231-0.17840.429495
39-0.133964-1.0290.15384
400.0533420.40970.341746
41-0.090164-0.69260.24565
42-0.124867-0.95910.170707
430.0164850.12660.449833
44-0.002117-0.01630.493542
450.0605520.46510.321783
46-0.079866-0.61350.270965
470.0234370.180.428876
480.0002440.00190.499256
49-0.076813-0.590.278717
50-0.079822-0.61310.271075
51-0.013634-0.10470.458476
520.0173670.13340.447166
530.0745180.57240.284618
54-0.036967-0.28390.388723
55-0.038235-0.29370.385014
56-0.049229-0.37810.353344
570.0346880.26640.395412
580.0096410.07410.47061
59NANANA
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/05/t1228483800utt44bpvwvufltg/1mzbx1228482848.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/05/t1228483800utt44bpvwvufltg/1mzbx1228482848.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/05/t1228483800utt44bpvwvufltg/24nk71228482848.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/05/t1228483800utt44bpvwvufltg/24nk71228482848.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1.9 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1.9 ; 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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