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Autocorrelatiefuncite d=0,D=0

*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: Fri, 10 Dec 2010 14:34:45 +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/10/t12919916084lagq40tz1asros.htm/, Retrieved Fri, 10 Dec 2010 15:33:28 +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/10/t12919916084lagq40tz1asros.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 «
1149822 1086979 1276674 1522522 1742117 1737275 1979900 2061036 1867943 1707752 1298756 1281814 1281151 1164976 1454329 1645288 1817743 1895785 2236311 2295951 2087315 1980891 1465446 1445026 1488120 1338333 1715789 1806090 2083316 2092278 2430800 2424894 2299016 2130688 1652221 1608162 1647074 1479691 1884978 2007898 2208954 2217164 2534291 2560312 2429069 2315077 1799608 1772590 1744799 1659093 2099821 2135736 2427894 2468882 2703217 2766841 2655236 2550373 2052097 1998055 1920748 1876694 2380930 2467402 2770771 2781340 3143926 3172235 2952540 2920877 2384552 2248987 2208616 2178756 2632870 2706905 3029745 3015402 3391414 3507805 3177852 3142961 2545815 2414007 2372578 2332664 2825328 2901478 3263955 3226738 3610786 3709274 3467185 3449646 2802951 2462530 2490645 2561520 3067554 3226951 3546493 3492787 3952263 3932072 3720284 3651555 2914972 2713514 2703997 2591373 3163748 3355137 3613702 3686773 etc...
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.92064613.84030
20.82132112.34720
30.67837810.19830
40.5331328.01470
50.4488566.74780
60.3944735.93020
70.4338996.52290
80.5023527.5520
90.6276719.4360
100.74745211.23670
110.82158512.35110
120.87088613.09230
130.80180312.05370
140.70781510.64080
150.5734858.62140
160.4347666.5360
170.3535295.31470
180.3018684.53815e-06
190.3352255.03950
200.4005926.02220
210.5199157.8160
220.6333839.52180
230.70241510.55960
240.74879711.25690
250.68211210.25440
260.5931858.91750
270.4660487.00620
280.3346065.03020
290.2556733.84367.9e-05
300.204213.06990.001202
310.234513.52550.000256
320.2924674.39678e-06
330.4017586.03970
340.5066717.61690
350.5692988.55840
360.6098459.1680
370.5454618.20010
380.4599216.91410
390.3393485.10150
400.2161653.24970.000666
410.1415322.12770.017223
420.0926591.3930.082498
430.1194731.79610.036909
440.1725052.59330.005063
450.2744244.12552.6e-05
460.3712485.58110
470.429586.4580
480.466727.01630
490.4072826.12280
500.3265834.90961e-06
510.2133453.20730.000767
520.0978721.47130.071296
530.0275560.41430.339539
54-0.016771-0.25210.400589
550.0086380.12990.448396
560.0587550.88330.189012
570.1545882.3240.010507
580.2456463.69290.000139
590.2996284.50445e-06
600.3350495.03690


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.92064613.84030
2-0.172356-2.59110.005095
3-0.334152-5.02341e-06
4-0.053358-0.80220.211654
50.441856.64250
60.1154291.73530.042027
70.405976.10310
80.0721641.08490.13957
90.4339496.52370
100.072221.08570.139384
110.0042180.06340.47475
120.1106791.66390.048762
13-0.424058-6.3750
14-0.068665-1.03230.151527
15-0.004487-0.06750.473142
16-0.08291-1.24640.106952
170.0348110.52330.300629
18-0.026362-0.39630.346125
19-0.040366-0.60680.272285
200.0209250.31460.376688
210.14722.21290.013952
22-0.005235-0.07870.468669
23-0.002799-0.04210.483238
240.0974191.46450.072219
25-0.220506-3.31490.000534
260.0256880.38620.349867
270.0207350.31170.377772
28-0.012059-0.18130.428151
29-0.034768-0.52270.300857
30-0.033456-0.5030.307744
31-0.036599-0.55020.291363
32-0.049673-0.74670.227997
330.0199130.29940.382472
340.0078560.11810.453046
35-0.008333-0.12530.450211
360.0087460.13150.447755
37-0.104635-1.5730.058557
380.0008640.0130.494826
390.0267770.40260.34383
400.0416230.62570.266059
41-0.031139-0.46810.320074
42-0.022706-0.34140.366578
43-0.039206-0.58940.278093
44-0.024483-0.36810.356588
450.014920.22430.411366
46-0.00813-0.12220.451418
470.0189050.28420.388259
48-0.006207-0.09330.46287
49-0.049964-0.75110.226682
50-0.02991-0.44970.326697
510.0164770.24770.402297
520.0146630.22040.412865
53-0.001118-0.01680.493301
540.0135250.20330.419529
55-0.038594-0.58020.281181
56-0.016794-0.25250.400456
570.0059450.08940.464431
580.0017470.02630.489535
59-0.00175-0.02630.48952
600.0321220.48290.314818
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/10/t12919916084lagq40tz1asros/1t20f1291991682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/10/t12919916084lagq40tz1asros/1t20f1291991682.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/10/t12919916084lagq40tz1asros/2t20f1291991682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/10/t12919916084lagq40tz1asros/2t20f1291991682.ps (open in new window)


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