*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, 17 May 2011 12:09:54 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t.htm/, Retrieved Tue, 17 May 2011 14:06:11 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,43 0,43 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,43 0,44 0,44 0,46 0,46 0,46 0,46 0,46 0,45 0,45 0,46 0,46 0,46 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Herman Ole Andreas Wold' @ www.yougetit.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.956781 8.1186 0 2 0.916376 7.7757 0 3 0.870342 7.3851 0 4 0.827123 7.0184 0 5 0.783903 6.6516 0 6 0.749127 6.3566 0 7 0.714351 6.0615 0 8 0.67676 5.7425 0 9 0.636355 5.3997 0 10 0.593136 5.0329 2e-06 11 0.547102 4.6423 8e-06 12 0.514007 4.3615 2.1e-05 13 0.475283 4.0329 6.8e-05 14 0.442187 3.7521 0.000176 15 0.407958 3.4616 0.000453 16 0.373729 3.1712 0.001116 17 0.320933 2.7232 0.004053 18 0.268137 2.2752 0.012936 19 0.215341 1.8272 0.035905 20 0.165359 1.4031 0.082439 21 0.115378 0.979 0.165426 22 0.092406 0.7841 0.217779 23 0.069435 0.5892 0.278795 24 0.053773 0.4563 0.324782 25 0.025172 0.2136 0.415733 26 -0.003428 -0.0291 0.488438 27 -0.034842 -0.2956 0.384175 28 -0.063443 -0.5383 0.296005 29 -0.094857 -0.8049 0.211766 30 -0.126272 -1.0715 0.143772 31 -0.163315 -1.3858 0.085046 32 -0.200359 -1.7001 0.046714 33 -0.237402 -2.0144 0.023851 34 -0.274445 -2.3287 0.011342 35 -0.311489 -2.6431 0.005038 36 -0.328832 -2.7902 0.003368 37 -0.346174 -2.9374 0.002221 38 -0.349445 -2.9651 0.002051 39 -0.352716 -2.9929 0.001892 40 -0.355987 -3.0207 0.001745 41 -0.362073 -3.0723 0.001499 42 -0.368158 -3.1239 0.001286 43 -0.374243 -3.1756 0.001101 44 -0.380329 -3.2272 0.000941 45 -0.386414 -3.2788 0.000804 46 -0.392499 -3.3305 0.000685 47 -0.398584 -3.3821 0.000583 48 -0.40467 -3.4337 0.000495 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.956781 8.1186 0 2 0.011191 0.095 0.462305 3 -0.086613 -0.7349 0.232384 4 0.004721 0.0401 0.484078 5 -0.017638 -0.1497 0.440723 6 0.072687 0.6168 0.269665 7 -0.013992 -0.1187 0.452912 8 -0.066273 -0.5623 0.287813 9 -0.05407 -0.4588 0.323881 10 -0.05476 -0.4647 0.321791 11 -0.051324 -0.4355 0.33225 12 0.128804 1.0929 0.139031 13 -0.087572 -0.7431 0.229928 14 0.011441 0.0971 0.461467 15 -0.025745 -0.2185 0.413846 16 -0.03897 -0.3307 0.370927 17 -0.21991 -1.866 0.033058 18 -0.054514 -0.4626 0.322536 19 -0.017456 -0.1481 0.44133 20 -0.013342 -0.1132 0.455088 21 -0.05696 -0.4833 0.315168 22 0.262867 2.2305 0.014416 23 0.008726 0.074 0.47059 24 0.03201 0.2716 0.393348 25 -0.155331 -1.318 0.095837 26 -0.0338 -0.2868 0.387543 27 -0.011073 -0.094 0.462701 28 -0.048358 -0.4103 0.34139 29 -0.070206 -0.5957 0.276617 30 -0.075118 -0.6374 0.262945 31 -0.155321 -1.3179 0.09585 32 -0.048711 -0.4133 0.340296 33 0.101698 0.8629 0.19552 34 -0.060344 -0.512 0.305096 35 -0.016271 -0.1381 0.445286 36 0.18268 1.5501 0.062752 37 0.011249 0.0954 0.462112 38 0.009685 0.0822 0.467366 39 -0.033841 -0.2871 0.387412 40 -0.071332 -0.6053 0.273452 41 0.005601 0.0475 0.481112 42 -0.065719 -0.5576 0.28941 43 0.071046 0.6028 0.274252 44 -0.005741 -0.0487 0.480643 45 -0.031482 -0.2671 0.395066 46 -0.103848 -0.8812 0.190577 47 0.0662 0.5617 0.288023 48 -0.075475 -0.6404 0.261965

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/1ie981305634193.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/1ie981305634193.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/28evj1305634193.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/28evj1305634193.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/3p73d1305634193.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/17/t1305633968sdn415jwg0a6v4t/3p73d1305634193.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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 (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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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