Home » date » 2009 » Jun » 02 »

Opgave 6bis, oefening 2: Jan Vanstraelen

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Tue, 02 Jun 2009 04:13:23 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/02/t1243937658lhlreluxmkkezsh.htm/, Retrieved Tue, 02 Jun 2009 12:14:18 +0200
 
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/2009/Jun/02/t1243937658lhlreluxmkkezsh.htm/},
    year = {2009},
}
@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 = {2009},
    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 «
11310 64305 15310 37299 21302 61308 72300 26303 18301 54305 66309 50301 31298 52291 87286 81288 14293 90302 50306 15310 44310 26314 98313 76310 25313 48309 95307 10320 87327 63328 34333 90333 81332 7342 30424 13344 88347 40339 23330 1339 10341 46342 81342 2342 76350 35368 93367 88377 39376 41366 77375 56382 79397 26385 73397 28404 98413 73414 47423 52431 24441 92439 90441 441 13448 18458 18459 69477 41491 10492 73508 82515 13525 55533 19550 85558 57563 60570 49568 51570 26561 61558 78548 77537 539 18540 47542 86542 81544 16543 22538 25538 99527 63518 95508 65496 5488 96475 81465 5463 81458 74445 21434 67427 27418 81407 82395 97359
 
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
1-0.458404-4.74183e-06
2-0.094866-0.98130.164329
30.0472990.48930.312827
4-0.098273-1.01650.155833
50.1441341.49090.06946
60.1740581.80050.037302
7-0.343941-3.55780.000279
80.1585531.64010.051962
9-0.0597-0.61750.269093
100.0540060.55860.288788
110.0059990.06210.475319
120.011760.12160.451705
13-0.113688-1.1760.121103
140.0756320.78230.21787
150.0208780.2160.414715
160.0401850.41570.33924
17-0.053071-0.5490.292084
18-0.053642-0.55490.290069
190.0272610.2820.389247
200.0140190.1450.442485
210.0778870.80570.21111
22-0.028492-0.29470.38439
23-0.109969-1.13750.12893
240.0031980.03310.486835
250.1024491.05970.145826
26-0.012144-0.12560.450133
270.0661690.68450.247582
28-0.12648-1.30830.096785
29-0.076713-0.79350.214613
300.1249461.29250.099492
310.0790390.81760.207704
32-0.136871-1.41580.079868
330.1183031.22370.11187
34-0.150339-1.55510.061436
350.0143160.14810.441277
360.1798831.86070.032765
37-0.09737-1.00720.158055
38-0.140946-1.4580.073891
390.2025222.09490.01927
40-0.154848-1.60180.056078
410.1529841.58250.058245
42-0.037325-0.38610.350099
43-0.112026-1.15880.124557
440.0291850.30190.38166
450.0704830.72910.233772
46-0.045829-0.47410.31821
470.0773730.80040.21264
48-0.049984-0.5170.3031
49-0.066236-0.68510.247366
50-0.004941-0.05110.479668
510.1662971.72020.044144
52-0.161961-1.67530.048394
530.130871.35370.089338
54-0.120179-1.24310.108267
55-0.053916-0.55770.289105
560.1827151.890.030731
57-0.062856-0.65020.258481
58-0.040355-0.41740.338598
59-0.006276-0.06490.474178
60-0.042151-0.4360.331853


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.458404-4.74183e-06
2-0.386142-3.99436e-05
3-0.282682-2.92410.002109
4-0.39831-4.12023.7e-05
5-0.269511-2.78780.00314
60.1538431.59140.057239
7-0.09488-0.98140.164293
80.0384370.39760.34586
9-0.052051-0.53840.295701
100.0093750.0970.461463
11-0.117057-1.21080.114311
12-0.011742-0.12150.451778
13-0.071321-0.73780.23114
14-0.120911-1.25070.106884
15-0.028314-0.29290.385091
160.0599470.62010.268256
170.0935170.96730.167777
18-0.024813-0.25670.398964
190.0240450.24870.402025
20-0.11313-1.17020.122255
21-0.000373-0.00390.498463
220.0541160.55980.2884
230.0113810.11770.453253
24-0.10196-1.05470.146974
25-0.027521-0.28470.38822
26-0.0091-0.09410.462589
270.102941.06480.144676
280.1184491.22520.111586
29-0.042872-0.44350.329158
30-0.072687-0.75190.226887
31-0.00305-0.03150.487445
32-0.113234-1.17130.12204
330.0577950.59780.275607
340.0538160.55670.289454
35-0.049042-0.50730.306496
360.061670.63790.262443
370.0830130.85870.196215
38-0.141445-1.46310.073183
39-0.001445-0.01490.494052
40-0.038487-0.39810.345669
410.0374480.38740.349628
420.001830.01890.492465
430.0500580.51780.302832
440.0090670.09380.462726
45-0.049378-0.51080.305281
46-0.048361-0.50030.308961
47-0.068889-0.71260.238825
480.0722980.74790.228094
490.0143580.14850.441104
50-0.031241-0.32320.373603
510.1282131.32620.093791
52-0.121275-1.25450.106201
530.0674680.69790.243378
54-0.003916-0.04050.483881
55-0.125199-1.29510.099042
560.0139080.14390.44294
57-0.025199-0.26070.397429
58-0.001916-0.01980.492111
59-0.076779-0.79420.214416
60-0.026435-0.27340.392518
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243937658lhlreluxmkkezsh/1gaoc1243937599.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243937658lhlreluxmkkezsh/1gaoc1243937599.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243937658lhlreluxmkkezsh/2qmkz1243937599.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243937658lhlreluxmkkezsh/2qmkz1243937599.ps (open in new window)


 
Parameters (Session):
par1 = 0.1 ; par2 = 0.99 ; par3 = 0.1 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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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