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ACF Uitvoer zonder Seizoenaliteit

*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: Mon, 22 Dec 2008 09:45:12 -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/22/t1229964409zf199i2tjt1fygw.htm/, Retrieved Mon, 22 Dec 2008 17:46:51 +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/2008/Dec/22/t1229964409zf199i2tjt1fygw.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},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
15916,4 16535,9 15796 14418,6 15044,5 14944,2 16754,8 14254 15454,9 15644,8 14568,3 12520,2 14803 15873,2 14755,3 12875,1 14291,1 14205,3 15859,4 15258,9 15498,6 15106,5 15023,6 12083 15761,3 16943 15070,3 13659,6 14768,9 14725,1 15998,1 15370,6 14956,9 15469,7 15101,8 11703,7 16283,6 16726,5 14968,9 14861 14583,3 15305,8 17903,9 16379,4 15420,3 17870,5 15912,8 13866,5 17823,2 17872 17420,4 16704,4 15991,2 16583,6 19123,5 17838,7 17209,4 18586,5 16258,1 15141,6 19202,1 17746,5 19090,1 18040,3 17515,5 17751,8 21072,4 17170 19439,5 19795,4 17574,9 16165,4 19464,6 19932,1 19961,2 17343,4 18924,2 18574,1 21350,6 18594,6 19823,1 20844,4 19640,2 17735,4 19813,6 22238,5 20682,2 17818,6 21872,1 22117 21865,9 23451,3 20953,7 22497,3
 
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'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2977052.69580.004259
20.4266083.86310.000111
30.5272644.77464e-06
40.2425512.19640.015444
50.2248992.03650.022461
60.3504583.17350.00106
70.0498760.45160.326359
80.1954191.76960.040256
90.2122691.92220.029028
100.0301680.27320.392701
110.0460880.41730.33876
120.0904210.81880.207638
13-0.020202-0.18290.427649
140.0971310.87960.190835
150.102760.93050.177414
16-0.020267-0.18350.42742
170.1755851.590.057842
180.1315461.19120.118505
190.0695340.62970.265336
200.1749951.58460.058448
210.0957330.86690.194264
22-0.009076-0.08220.46735
230.2576792.33340.011039
24-0.102041-0.9240.179093
250.0276170.25010.401575
260.08310.75250.226953
27-0.062751-0.56820.285713
28-0.087087-0.78860.216308
290.0010890.00990.496077
30-0.206071-1.86610.032805
31-0.071202-0.64480.26044
32-0.069424-0.62870.265658
33-0.185676-1.68140.048248
34-0.07882-0.71370.238706
35-0.03926-0.35550.361558
36-0.110769-1.00310.159393
370.0008460.00770.496953
38-0.007147-0.06470.474278
39-0.048589-0.440.33055
400.0717470.64970.258852
410.0493530.44690.32806
42-0.042045-0.38070.352194
430.0660860.59840.275601
440.0622120.56340.287364
45-0.086882-0.78670.216849
460.1012290.91670.181003
47-0.076468-0.69240.245308
48-0.126017-1.14110.128568
490.0070510.06380.474624
50-0.135409-1.22620.111821
51-0.170805-1.54670.062893
52-0.063128-0.57160.284563
53-0.166977-1.5120.067184
54-0.115167-1.04290.150034
55-0.075639-0.68490.247657
56-0.181473-1.64330.052074
57-0.080525-0.72920.233984
58-0.081578-0.73870.231093
59-0.118043-1.06890.144121
60-0.032984-0.29870.382969


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2977052.69580.004259
20.3708473.35820.000596
30.4286793.88190.000104
4-0.037341-0.33810.368061
5-0.182594-1.65350.051031
60.0986790.89360.187081
7-0.124515-1.12750.131404
80.0625010.5660.286479
90.1028470.93130.17721
10-0.031305-0.28350.388762
11-0.168477-1.52560.065476
12-0.064839-0.58710.279362
130.0757390.68580.247371
140.182491.65250.051127
150.1343691.21680.113593
16-0.11844-1.07250.143316
170.0451060.40850.342003
180.0550710.49870.309665
190.0608560.55110.29154
200.0406620.36820.356834
21-0.071888-0.6510.258443
22-0.221566-2.00640.024057
230.1636391.48180.071111
24-0.172144-1.55880.061444
250.0285920.25890.398177
260.0026840.02430.490333
27-0.000369-0.00330.498672
28-0.122082-1.10550.136088
29-0.101047-0.9150.181432
300.0051750.04690.48137
310.0819280.74190.230137
320.0413260.37420.354601
33-0.075562-0.68420.247875
340.0131470.1190.452764
35-0.01767-0.160.436634
360.0732680.66350.254446
370.0674110.61040.271631
380.0291870.26430.396105
390.0135520.12270.451316
40-0.06284-0.5690.285443
410.0188270.17050.432523
42-0.042596-0.38570.350349
430.0257030.23280.408267
440.086610.78430.217566
45-0.119276-1.08010.141635
46-0.057742-0.52290.301236
470.0073570.06660.473524
48-0.115002-1.04140.150379
490.0474270.42950.334354
50-0.012505-0.11320.45506
510.0242770.21980.41327
52-0.102073-0.92430.179019
53-0.021233-0.19230.424002
540.035480.32130.374406
550.042470.38460.35077
56-0.066622-0.60330.273991
57-0.017649-0.15980.436707
58-0.076148-0.68960.246211
59-0.031306-0.28350.388757
600.1155131.0460.149314
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229964409zf199i2tjt1fygw/1iuqn1229964310.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229964409zf199i2tjt1fygw/1iuqn1229964310.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229964409zf199i2tjt1fygw/2p3hr1229964310.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229964409zf199i2tjt1fygw/2p3hr1229964310.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; 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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