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Autocorrelatiefunctie D=1

*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: Wed, 22 Dec 2010 19:04:52 +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/22/t12930445688g8dlxaupmr30az.htm/, Retrieved Wed, 22 Dec 2010 20:02:48 +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/22/t12930445688g8dlxaupmr30az.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 «
27951 29781 32914 33488 35652 36488 35387 35676 34844 32447 31068 29010 29812 30951 32974 32936 34012 32946 31948 30599 27691 25073 23406 22248 22896 25317 26558 26471 27543 26198 24725 25005 23462 20780 19815 19761 21454 23899 24939 23580 24562 24696 23785 23812 21917 19713 19282 18788 21453 24482 27474 27264 27349 30632 29429 30084 26290 24379 23335 21346 21106 24514 28353 30805 31348 34556 33855 34787 32529 29998 29257 28155 30466 35704 39327 39351 42234 43630 43722 43121 37985 37135 34646 33026 35087 38846 42013 43908 42868 44423 44167 43636 44382 42142 43452 36912 42413 45344 44873 47510 49554 47369 45998 48140 48441 44928 40454 38661 37246 36843 36424 37594 38144 38737 34560 36080 33508 35462 33374 32110 35533 35532 37903 36763 40399 44164 44496 43110 43880 43930 44327
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time40 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.209778-2.27880.01224
20.1873972.03570.022012
30.0427310.46420.321687
40.1552671.68660.047158
50.0105910.1150.454301
6-0.010445-0.11350.454928
70.0640420.69570.244001
80.0740830.80470.211293
9-0.141825-1.54060.063044
100.0255320.27730.391
110.0855690.92950.177258
12-0.400937-4.35531.4e-05
130.243522.64530.004637
14-0.250189-2.71780.003782
150.0583090.63340.263849
16-0.216953-2.35670.010043
17-0.063648-0.69140.245339
180.0339030.36830.356663
19-0.030663-0.33310.369829
20-0.079811-0.8670.193858
210.1875242.0370.021942
22-0.151613-1.64690.051116
230.0791830.86010.195726
24-0.026099-0.28350.388642
25-0.068028-0.7390.230694
260.2073262.25210.013082
27-0.134602-1.46220.073178
280.1533911.66630.049158
29-0.041542-0.45130.326314
300.0277750.30170.3817
310.0184780.20070.420629
320.0008480.00920.496335
33-0.102036-1.10840.134972
340.0418290.45440.325196
35-0.115475-1.25440.106092
36-0.025375-0.27560.391654
37-0.03766-0.40910.341608
38-0.122046-1.32580.09374
390.1180861.28270.101049
40-0.144107-1.56540.060083
410.1129811.22730.111079
42-0.086236-0.93680.175396
43-0.052395-0.56920.285166
44-0.014902-0.16190.435838
45-0.044049-0.47850.316593
460.0090950.09880.460734
47-0.025743-0.27960.39012
48-0.028834-0.31320.377335
490.034340.3730.354898
500.0759990.82560.205359
51-0.079988-0.86890.193336
520.0654070.71050.239398
53-0.076009-0.82570.205329
540.0884560.96090.16929
55-0.041802-0.45410.325301
560.0228380.24810.40225
57-0.033008-0.35860.360282
580.0190060.20650.418397
59-0.021178-0.23010.409225
600.0021810.02370.490571


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.209778-2.27880.01224
20.1499911.62930.052956
30.1151561.25090.106721
40.1689911.83570.034459
50.0509090.5530.290652
6-0.064887-0.70490.241144
70.009430.10240.459291
80.0801320.87050.19291
9-0.140404-1.52520.064945
10-0.063747-0.69250.245
110.1127511.22480.111546
12-0.415301-4.51138e-06
130.1590441.72770.043333
14-0.087707-0.95270.171335
15-0.063559-0.69040.245642
16-0.054673-0.59390.276859
17-0.143307-1.55670.061109
180.0536930.58330.280419
190.1380011.49910.068263
200.0024120.02620.489569
210.1418671.54110.062989
22-0.053909-0.58560.27963
230.0042740.04640.481524
24-0.138165-1.50090.068031
25-0.013914-0.15110.440059
260.0909420.98790.162616
27-0.018096-0.19660.42225
28-0.008855-0.09620.461766
29-0.08057-0.87520.191618
300.0354990.38560.350238
31-0.010837-0.11770.453244
32-0.050831-0.55220.29094
33-0.044366-0.48190.315372
34-0.174435-1.89480.03028
350.0900760.97850.164922
36-0.187334-2.0350.022047
370.0718820.78080.218232
380.0177150.19240.423865
39-0.020257-0.220.413108
400.0541910.58870.278605
410.0269660.29290.385048
420.0217040.23580.407013
43-0.062857-0.68280.248035
44-0.069781-0.7580.224975
45-0.106003-1.15150.125931
46-0.006455-0.07010.472111
47-0.049793-0.54090.294803
48-0.135105-1.46760.072434
490.0384120.41730.338622
500.0690940.75060.227206
51-0.036374-0.39510.346733
52-0.043307-0.47040.319456
53-0.032468-0.35270.362474
540.0315260.34250.366305
550.0186820.20290.419767
560.004190.04550.481888
57-0.102257-1.11080.134456
58-0.000635-0.00690.497256
59-0.052213-0.56720.285835
60-0.162627-1.76660.039942
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/1gcx91293044650.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/1gcx91293044650.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/294xu1293044650.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/294xu1293044650.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/394xu1293044650.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t12930445688g8dlxaupmr30az/394xu1293044650.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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 (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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