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autocorrelatie functie

*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: Sat, 18 Dec 2010 19:29:00 +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/18/t12927004380pt3ve6f73cl91m.htm/, Retrieved Sat, 18 Dec 2010 20:27:20 +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/18/t12927004380pt3ve6f73cl91m.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 «
101,76 102,37 102,38 102,86 102,87 102,92 102,95 103,02 104,08 104,16 104,24 104,33 104,73 104,86 105,03 105,62 105,63 105,63 105,94 106,61 107,69 107,78 107,93 108,48 108,14 108,48 108,48 108,89 108,93 109,21 109,47 109,80 111,73 111,85 112,12 112,15 112,17 112,67 112,80 113,44 113,53 114,53 114,51 115,05 116,67 117,07 116,92 117,00 117,02 117,35 117,36 117,82 117,88 118,24 118,50 118,80 119,76 120,09 120,16
 
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'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9504477.30050
20.9014426.92410
30.8514316.540
40.8061296.1920
50.7602985.840
60.7128195.47530
70.6656355.11282e-06
80.6154074.7277e-06
90.5709314.38542.4e-05
100.52414.02578.2e-05
110.4770983.66470.000266
120.4278433.28630.000856
130.3750092.88050.002763
140.3193052.45260.008579
150.2642282.02960.023459
160.2185111.67840.049278
170.1743011.33880.092881
180.1272320.97730.166208
190.0850590.65340.258033
200.0438620.33690.368691
210.0096160.07390.470686
22-0.025535-0.19610.422589
23-0.059458-0.45670.324781
24-0.092096-0.70740.241051
25-0.130234-1.00030.160614
26-0.167244-1.28460.101972
27-0.205357-1.57740.060028
28-0.232184-1.78340.039829
29-0.257999-1.98170.026087
30-0.283326-2.17630.016775
31-0.30696-2.35780.010859
32-0.330769-2.54070.006857
33-0.344336-2.64490.005228
34-0.358799-2.7560.003886
35-0.371077-2.85030.003004
36-0.38592-2.96430.002185
37-0.400001-3.07250.001605
38-0.412081-3.16530.001226
39-0.424019-3.2570.000935
40-0.42779-3.28590.000857
41-0.428346-3.29020.000846
42-0.423717-3.25460.000941
43-0.419796-3.22450.001029
44-0.414304-3.18230.001166
45-0.398739-3.06280.001651
46-0.380757-2.92470.002443
47-0.363157-2.78950.003549
48-0.343354-2.63740.005333


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9504477.30050
2-0.019725-0.15150.440045
3-0.036167-0.27780.391068
40.021680.16650.434157
5-0.030049-0.23080.40913
6-0.044219-0.33970.367663
7-0.022466-0.17260.431792
8-0.060024-0.46110.323228
90.0270150.20750.418164
10-0.051411-0.39490.347172
11-0.036593-0.28110.389819
12-0.04937-0.37920.352942
13-0.073872-0.56740.286289
14-0.07071-0.54310.294542
15-0.035247-0.27070.39377
160.0492070.3780.353405
17-0.018337-0.14090.444234
18-0.070758-0.54350.294417
190.0202430.15550.438484
20-0.027423-0.21060.416947
210.0260140.19980.421155
22-0.041732-0.32060.374842
23-0.027643-0.21230.416289
24-0.008492-0.06520.474105
25-0.097484-0.74880.228479
26-0.040095-0.3080.379592
27-0.050702-0.38940.349174
280.054380.41770.338841
29-0.02727-0.20950.417405
30-0.044469-0.34160.366943
31-0.008115-0.06230.475255
32-0.044737-0.34360.366172
330.0464730.3570.361196
34-0.036893-0.28340.388938
35-0.020568-0.1580.437505
36-0.036171-0.27780.391056
37-0.036474-0.28020.390165
38-0.019317-0.14840.441276
39-0.033821-0.25980.397967
400.0248620.1910.424603
410.0057010.04380.48261
420.0148850.11430.45468
43-0.017355-0.13330.447202
44-0.015842-0.12170.451782
450.065280.50140.30897
460.0130190.10.460341
47-0.028-0.21510.415227
480.0446590.3430.366398
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/18/t12927004380pt3ve6f73cl91m/1sr5q1292700538.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t12927004380pt3ve6f73cl91m/1sr5q1292700538.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/18/t12927004380pt3ve6f73cl91m/2sr5q1292700538.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t12927004380pt3ve6f73cl91m/2sr5q1292700538.ps (open in new window)


 
Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
 
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 (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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