*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Wed, 04 May 2011 16:48:57 +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/04/t13045275958p49aw0ighvlvlg.htm/, Retrieved Wed, 04 May 2011 18:46:39 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

31.900 31.815 31.075 31.070 31.300 31.410 30.310 31.440 31.355 31.380 31.975 31.905 32.565 32.780 32.850 32.910 32.910 33.755 34.130 34.330 34.120 33.600 33.715 33.535 33.745 34.295 33.940 34.245 34.395 33.640 33.890 33.905 33.930 33.975 33.880 33.800 33.165 33.660 33.545 33.590 33.810 33.720 33.660 33.915 34.265 34.175 33.735 33.855 34.210 33.950 33.130 32.195 33.160 33.255 32.260 31.795 31.875 31.985 31.835 32.200 32.275 32.515 32.700 32.680 32.135 31.460 30.755 31.090 31.270 31.110 30.835 31.025 30.800 30.790

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 2 seconds R Server 'George Udny Yule' @ 216.218.223.82 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.046533 -0.3976 0.34605 2 -0.176619 -1.509 0.067803 3 0.046613 0.3983 0.345799 4 0.058459 0.4995 0.309474 5 0.122876 1.0498 0.148625 6 -0.108458 -0.9267 0.178578 7 0.002584 0.0221 0.491223 8 0.021369 0.1826 0.42782 9 0.008357 0.0714 0.471636 10 0.088168 0.7533 0.226845 11 -0.149265 -1.2753 0.10312 12 -0.017408 -0.1487 0.441087 13 -0.022553 -0.1927 0.423868 14 -0.043429 -0.3711 0.355836 15 0.29707 2.5382 0.006638 16 -0.064333 -0.5497 0.292115 17 -0.109255 -0.9335 0.176825 18 0.051721 0.4419 0.329933 19 -0.03126 -0.2671 0.395078 20 0.137355 1.1736 0.122193 21 -0.023048 -0.1969 0.422219 22 -0.068956 -0.5892 0.278785 23 -0.017283 -0.1477 0.441506 24 -0.045287 -0.3869 0.349966 25 0.054282 0.4638 0.322089 26 -0.09106 -0.778 0.219537 27 0.04258 0.3638 0.358528 28 0.034002 0.2905 0.386125 29 -0.0655 -0.5596 0.288721 30 0.16613 1.4194 0.080017 31 -0.057052 -0.4875 0.313698 32 -0.062308 -0.5324 0.298046 33 -0.037398 -0.3195 0.375118 34 0.037413 0.3197 0.375072 35 0.051341 0.4387 0.331102 36 0.010183 0.087 0.465453 37 -0.051138 -0.4369 0.331727 38 -0.139247 -1.1897 0.119004 39 -0.095784 -0.8184 0.207901 40 0.057967 0.4953 0.310949 41 -0.089002 -0.7604 0.224723 42 -0.082035 -0.7009 0.242795 43 0.019457 0.1662 0.434214 44 0.024917 0.2129 0.416003 45 0.142441 1.217 0.113759 46 -0.12153 -1.0384 0.151267 47 -0.138732 -1.1853 0.119867 48 0.043451 0.3712 0.355765 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.046533 -0.3976 0.34605 2 -0.179173 -1.5309 0.065064 3 0.029597 0.2529 0.400537 4 0.031906 0.2726 0.392962 5 0.146095 1.2482 0.107966 6 -0.085066 -0.7268 0.234836 7 0.037937 0.3241 0.373381 8 -0.028261 -0.2415 0.404938 9 0.015423 0.1318 0.447762 10 0.080554 0.6883 0.246738 11 -0.122832 -1.0495 0.14871 12 -0.013402 -0.1145 0.454574 13 -0.085616 -0.7315 0.233408 14 -0.04858 -0.4151 0.339656 15 0.296665 2.5347 0.006699 16 -0.008237 -0.0704 0.472044 17 -0.030877 -0.2638 0.396334 18 0.017132 0.1464 0.442016 19 -0.0999 -0.8535 0.198073 20 0.109738 0.9376 0.17577 21 0.065038 0.5557 0.290061 22 -0.063559 -0.543 0.294375 23 -0.049316 -0.4214 0.337368 24 -0.106441 -0.9094 0.183058 25 -0.045641 -0.39 0.348852 26 0.0319 0.2726 0.392981 27 0.097679 0.8346 0.203341 28 0.024548 0.2097 0.417227 29 -0.021005 -0.1795 0.429034 30 0.036705 0.3136 0.377357 31 -0.018161 -0.1552 0.438558 32 0.034108 0.2914 0.38578 33 -0.091165 -0.7789 0.219275 34 0.05465 0.4669 0.320971 35 -0.099545 -0.8505 0.19891 36 0.04747 0.4056 0.343117 37 -0.018118 -0.1548 0.438703 38 -0.138291 -1.1816 0.120608 39 -0.111784 -0.9551 0.171345 40 -0.023022 -0.1967 0.422303 41 -0.081984 -0.7005 0.242929 42 -0.043762 -0.3739 0.35478 43 0.019781 0.169 0.433129 44 0.033594 0.287 0.387452 45 0.123467 1.0549 0.147475 46 -0.078626 -0.6718 0.251923 47 -0.10799 -0.9227 0.179609 48 -0.004226 -0.0361 0.485649

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/1nb1h1304527734.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/1nb1h1304527734.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/27axq1304527734.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/27axq1304527734.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/3sanr1304527734.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/04/t13045275958p49aw0ighvlvlg/3sanr1304527734.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; 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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