*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: Mon, 07 Dec 2009 12:23:24 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/07/t12602138517snuxspx429phkf.htm/, Retrieved Mon, 07 Dec 2009 20:24:14 +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/2009/Dec/07/t12602138517snuxspx429phkf.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 «

17 18 23.8 25.5 25.6 23.7 22 21.3 20.7 20.4 20.3 20.4 19.8 19.5 23.1 23.5 23.5 22.9 21.9 21.5 20.5 20.2 19.4 19.2 18.8 18.8 22.6 23.3 23 21.4 19.9 18.8 18.6 18.4 18.6 19.9 19.2 18.4 21.1 20.5 19.1 18.1 17 17.1 17.4 16.8 15.3 14.3 13.4 15.3 22.1 23.7 22.2 19.5 16.6 17.3 19.8 21.2 21.5 20.6 19.1 19.6 23.5 24

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 'Gwilym Jenkins' @ 72.249.127.135 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.742189 5.9375 0 2 0.329889 2.6391 0.005214 3 0.070328 0.5626 0.287829 4 -0.002153 -0.0172 0.493155 5 0.076971 0.6158 0.270116 6 0.145741 1.1659 0.123985 7 0.117722 0.9418 0.174925 8 0.044371 0.355 0.36189 9 0.047513 0.3801 0.352563 10 0.147684 1.1815 0.120893 11 0.309489 2.4759 0.007973 12 0.401596 3.2128 0.00103 13 0.226903 1.8152 0.037087 14 0.000301 0.0024 0.499042 15 -0.111802 -0.8944 0.187226 16 -0.166003 -1.328 0.094444 17 -0.16946 -1.3557 0.089983 18 -0.176356 -1.4108 0.081566 19 -0.200337 -1.6027 0.056963 20 -0.194666 -1.5573 0.062162 21 -0.116084 -0.9287 0.178275 22 0.016054 0.1284 0.449104 23 0.152786 1.2223 0.113041 24 0.202618 1.6209 0.054974 25 0.036487 0.2919 0.385654 26 -0.16395 -1.3116 0.09717 27 -0.255324 -2.0426 0.022608 28 -0.279961 -2.2397 0.014296 29 -0.245499 -1.964 0.026939 30 -0.199213 -1.5937 0.057964 31 -0.175231 -1.4018 0.082897 32 -0.156504 -1.252 0.107558 33 -0.105649 -0.8452 0.200576 34 -0.03478 -0.2782 0.390862 35 0.037537 0.3003 0.382461 36 0.055889 0.4471 0.328151 37 -0.069966 -0.5597 0.288808 38 -0.201191 -1.6095 0.056212 39 -0.223618 -1.7889 0.039178 40 -0.203076 -1.6246 0.05458 41 -0.163075 -1.3046 0.09835 42 -0.14782 -1.1826 0.120678 43 -0.163535 -1.3083 0.097728 44 -0.15755 -1.2604 0.10605 45 -0.087394 -0.6992 0.243494 46 0.039456 0.3156 0.376648 47 0.157887 1.2631 0.105569 48 0.185022 1.4802 0.071866 49 0.053435 0.4275 0.335233 50 -0.095677 -0.7654 0.223418 51 -0.116427 -0.9314 0.17757 52 -0.063359 -0.5069 0.306992 53 0.019903 0.1592 0.436998 54 0.070726 0.5658 0.286751 55 0.056135 0.4491 0.327446 56 0.021007 0.1681 0.433533 57 0.013448 0.1076 0.457331 58 0.045743 0.3659 0.357806 59 0.086533 0.6923 0.245638 60 0.085544 0.6843 0.248113 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.742189 5.9375 0 2 -0.491935 -3.9355 0.000104 3 0.206048 1.6484 0.052088 4 -0.007766 -0.0621 0.475328 5 0.200337 1.6027 0.056963 6 -0.130091 -1.0407 0.150959 7 0.009634 0.0771 0.469402 8 -0.008552 -0.0684 0.472835 9 0.212899 1.7032 0.046692 10 0.065599 0.5248 0.300772 11 0.257513 2.0601 0.02173 12 -0.060976 -0.4878 0.313676 13 -0.359024 -2.8722 0.002761 14 0.28644 2.2915 0.012617 15 -0.207483 -1.6599 0.050918 16 -0.161882 -1.2951 0.099977 17 -0.115223 -0.9218 0.180051 18 -0.068354 -0.5468 0.293197 19 -0.012441 -0.0995 0.460514 20 -0.005597 -0.0448 0.482214 21 0.016347 0.1308 0.448181 22 0.10444 0.8355 0.203267 23 0.103662 0.8293 0.20501 24 -0.079507 -0.6361 0.263503 25 -0.10612 -0.849 0.199535 26 0.028132 0.2251 0.411327 27 -0.120218 -0.9617 0.169899 28 0.032967 0.2637 0.396416 29 -0.089645 -0.7172 0.237942 30 0.03333 0.2666 0.395302 31 -0.031844 -0.2548 0.399866 32 -0.031671 -0.2534 0.400397 33 0.002884 0.0231 0.490833 34 -0.085832 -0.6867 0.247389 35 0.023537 0.1883 0.425621 36 -0.124707 -0.9977 0.161101 37 -0.003181 -0.0254 0.489889 38 -0.030791 -0.2463 0.403109 39 0.078056 0.6244 0.267276 40 -0.036965 -0.2957 0.384201 41 0.014217 0.1137 0.4549 42 -0.100802 -0.8064 0.211495 43 -0.021772 -0.1742 0.431139 44 -0.008088 -0.0647 0.474307 45 -0.014957 -0.1197 0.452564 46 0.125316 1.0025 0.159932 47 -0.020795 -0.1664 0.434198 48 0.025388 0.2031 0.41985 49 -0.020741 -0.1659 0.434369 50 0.013439 0.1075 0.457359 51 0.067949 0.5436 0.294305 52 -0.021071 -0.1686 0.433333 53 0.047616 0.3809 0.352258 54 -0.031839 -0.2547 0.39988 55 -0.004243 -0.0339 0.486515 56 -0.091118 -0.7289 0.234348 57 -0.044738 -0.3579 0.360797 58 -0.097673 -0.7814 0.218729 59 -0.070381 -0.563 0.287684 60 -0.014195 -0.1136 0.45497

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/07/t12602138517snuxspx429phkf/14an41260213802.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/07/t12602138517snuxspx429phkf/14an41260213802.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/07/t12602138517snuxspx429phkf/2z3pq1260213802.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/07/t12602138517snuxspx429phkf/2z3pq1260213802.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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')

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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