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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 31 Mar 2011 11:12:04 +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/Mar/31/t1301569717q682iqxa73d3c2k.htm/, Retrieved Thu, 31 Mar 2011 13:08:38 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

25525 26197 26555 57364 62022 34392 37258 76262 50423 32959 38601 31705 40754 41827 43983 91590 99026 54911 59487 121762 80508 52623 61632 50621 70206 68382 73039 157780 170589 94594 102477 209757 138689 90652 106172 87204 110160 112200 113832 245616 265608 147288 159528 326400 215832 141168 165240 135864

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.770252 5.3365 1e-06 2 0.577927 4.004 0.000108 3 0.613911 4.2533 4.8e-05 4 0.57209 3.9636 0.000122 5 0.434476 3.0101 0.002077 6 0.348775 2.4164 0.009764 7 0.333885 2.3132 0.01252 8 0.385945 2.6739 0.005109 9 0.365417 2.5317 0.00734 10 0.254456 1.7629 0.04214 11 0.319063 2.2105 0.015934 12 0.404402 2.8018 0.003653 13 0.226167 1.5669 0.061851 14 0.07379 0.5112 0.305766 15 0.096422 0.668 0.253656 16 0.067435 0.4672 0.321234 17 -0.037697 -0.2612 0.397539 18 -0.107589 -0.7454 0.229833 19 -0.123361 -0.8547 0.19849 20 -0.086782 -0.6012 0.275253 21 -0.104519 -0.7241 0.236251 22 -0.18393 -1.2743 0.104345 23 -0.140267 -0.9718 0.168012 24 -0.0875 -0.6062 0.273613 25 -0.195018 -1.3511 0.091496 26 -0.290194 -2.0105 0.025006 27 -0.2653 -1.8381 0.036124 28 -0.261459 -1.8114 0.038166 29 -0.312894 -2.1678 0.017582 30 -0.343156 -2.3775 0.010732 31 -0.340919 -2.362 0.011141 32 -0.3004 -2.0812 0.021385 33 -0.293328 -2.0322 0.023842 34 -0.320805 -2.2226 0.015494 35 -0.281657 -1.9514 0.028431 36 -0.241937 -1.6762 0.050102 37 -0.275332 -1.9076 0.031221 38 -0.303622 -2.1036 0.020341 39 -0.269429 -1.8667 0.034032 40 -0.227463 -1.5759 0.060808 41 -0.222484 -1.5414 0.064892 42 -0.21093 -1.4614 0.075215 43 -0.183589 -1.2719 0.104761 44 -0.134677 -0.9331 0.177727 45 -0.099555 -0.6897 0.24684 46 -0.069257 -0.4798 0.316764 47 -0.029362 -0.2034 0.419831 48 NA NA NA Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.770252 5.3365 1e-06 2 -0.037771 -0.2617 0.397342 3 0.44577 3.0884 0.001671 4 -0.136961 -0.9489 0.173714 5 -0.028302 -0.1961 0.422688 6 -0.098001 -0.679 0.250209 7 0.056332 0.3903 0.349028 8 0.267296 1.8519 0.035099 9 -0.052661 -0.3648 0.358413 10 -0.107902 -0.7476 0.229183 11 0.276789 1.9176 0.030558 12 -0.070122 -0.4858 0.314653 13 -0.35817 -2.4815 0.008319 14 -0.076556 -0.5304 0.299142 15 -0.050667 -0.351 0.363549 16 -0.020869 -0.1446 0.442822 17 -0.014606 -0.1012 0.45991 18 -0.016617 -0.1151 0.454414 19 -0.04554 -0.3155 0.376871 20 -0.047915 -0.332 0.37068 21 -0.006045 -0.0419 0.483382 22 0.009461 0.0655 0.474005 23 0.005479 0.038 0.48494 24 -0.058905 -0.4081 0.342506 25 -0.01491 -0.1033 0.459077 26 -0.085923 -0.5953 0.277222 27 -0.032723 -0.2267 0.410804 28 0.010556 0.0731 0.471001 29 -0.0088 -0.061 0.475819 30 0.014775 0.1024 0.459446 31 -0.071163 -0.493 0.31212 32 -0.027404 -0.1899 0.425109 33 -0.011641 -0.0807 0.468028 34 0.015425 0.1069 0.457671 35 -0.020752 -0.1438 0.44314 36 -0.044325 -0.3071 0.380049 37 0.057048 0.3952 0.347207 38 -0.032251 -0.2234 0.412069 39 -0.008944 -0.062 0.475423 40 0.069359 0.4805 0.316517 41 -0.019438 -0.1347 0.446718 42 0.059317 0.411 0.341464 43 -0.04175 -0.2893 0.386817 44 0.018764 0.13 0.448555 45 0.025545 0.177 0.430133 46 0.06938 0.4807 0.316464 47 -0.001708 -0.0118 0.495305 48 NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/1s8ev1301569920.png (open in new window) http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/1s8ev1301569920.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/203w01301569920.png (open in new window) http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/203w01301569920.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/39x031301569920.png (open in new window) http://www.freestatistics.org/blog/date/2011/Mar/31/t1301569717q682iqxa73d3c2k/39x031301569920.ps (open in new window)

Parameters (Session):

par1 = 12 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 0 ; par7 = 1 ; par8 = 1 ; par9 = 0 ; par10 = FALSE ;

Parameters (R input):

par1 = 48 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ; par9 = 0 ; par10 = FALSE ;

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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