*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 19 May 2011 17:47:08 +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/19/t1305827123sx501uasafitypk.htm/, Retrieved Thu, 19 May 2011 19:45:27 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

19097.1 19304.6 19601.7 16006.9 17681.2 19790.4 17014.2 17424.5 18908.9 15692.1 15160 15794.3 16032.1 16065 16236.8 12521 14762.1 15446.9 13635 14212.6 15021.7 14134.3 13721.4 14384.5 15638.6 19711.6 20359.8 16141.4 20056.9 20605.5 19325.8 20547.7 19211.2 19009.5 18746.8 16471.5 18957.2 20515.2 18374.4 16192.9 18147.5 19301.4 18344.7 17183.6 19630 17167.2 17428.5 16016.5 18466.5 18406.6 18174.1 14851.9 16260.7 18329.6 18003.8 15903.8 19554.2 16554.2 16198.9 16571.8 17535.2 16198.1 17487.5 13768 14915.8 17160.9 15607.4 16181.5 17413.2 15116.3 14544.5 15050.6 15535.4 15919.3 15853.1 12336.4 14355.5 16040.8 13867.7 14656.6

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 -0.332431 -2.9547 0.002061 2 -0.323114 -2.8719 0.002618 3 0.233533 2.0757 0.020588 4 0.040039 0.3559 0.361443 5 -0.141719 -1.2596 0.105756 6 0.24723 2.1974 0.01546 7 -0.255625 -2.272 0.012902 8 0.169775 1.509 0.067645 9 0.105126 0.9344 0.176476 10 -0.362382 -3.2209 0.000928 11 -0.115078 -1.0228 0.154754 12 0.620047 5.5111 0 13 -0.25595 -2.2749 0.012811 14 -0.192926 -1.7148 0.045155 15 0.056077 0.4984 0.309785 16 0.056263 0.5001 0.309205 17 -0.049016 -0.4357 0.332135 18 0.083782 0.7447 0.229341 19 -0.160904 -1.4301 0.078309 20 0.189695 1.686 0.047866 21 0.014665 0.1303 0.448314 22 -0.305379 -2.7143 0.004076 23 0.014274 0.1269 0.449683 24 0.34716 3.0856 0.0014 25 -0.069219 -0.6152 0.270085 26 -0.196667 -1.748 0.042173 27 -0.038398 -0.3413 0.366896 28 0.191233 1.6997 0.04656 29 -0.063352 -0.5631 0.287487 30 -0.016795 -0.1493 0.440859 31 0.018511 0.1645 0.434869 32 0.056778 0.5047 0.307605 33 -0.02332 -0.2073 0.418165 34 -0.086191 -0.7661 0.222956 35 -0.130729 -1.1619 0.124379 36 0.301193 2.6771 0.004515 37 0.026797 0.2382 0.406182 38 -0.295264 -2.6244 0.005209 39 0.066453 0.5907 0.27822 40 0.170363 1.5142 0.06698 41 -0.172817 -1.536 0.064263 42 0.092846 0.8252 0.205862 43 0.032717 0.2908 0.385986 44 -0.067536 -0.6003 0.27502 45 0.042597 0.3786 0.352997 46 -0.023532 -0.2092 0.417431 47 -0.192262 -1.7089 0.045702 48 0.319021 2.8355 0.002904 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.332431 -2.9547 0.002061 2 -0.487499 -4.333 2.1e-05 3 -0.130223 -1.1574 0.125288 4 -0.076914 -0.6836 0.248106 5 -0.093098 -0.8275 0.205231 6 0.259747 2.3087 0.011788 7 -0.157617 -1.4009 0.082575 8 0.281127 2.4987 0.00727 9 0.137842 1.2252 0.112076 10 -0.237104 -2.1074 0.019126 11 -0.493206 -4.3837 1.8e-05 12 0.156933 1.3949 0.083485 13 0.155882 1.3855 0.084898 14 0.141276 1.2557 0.106464 15 -0.141997 -1.2621 0.105313 16 -0.063544 -0.5648 0.286907 17 -0.077595 -0.6897 0.246208 18 -0.127795 -1.1359 0.129723 19 -0.02858 -0.254 0.400068 20 -0.034611 -0.3076 0.379588 21 0.045941 0.4083 0.342067 22 -0.083175 -0.7393 0.230965 23 0.029809 0.265 0.395868 24 -0.159549 -1.4181 0.080047 25 0.11659 1.0363 0.151619 26 -0.112086 -0.9962 0.161088 27 -0.096929 -0.8615 0.195778 28 0.097674 0.8681 0.193972 29 -0.015243 -0.1355 0.446287 30 0.108418 0.9636 0.169083 31 0.041311 0.3672 0.357234 32 -0.064714 -0.5752 0.283399 33 -0.20333 -1.8072 0.037266 34 0.07389 0.6567 0.256625 35 -0.178193 -1.5838 0.058616 36 0.072217 0.6419 0.261404 37 -0.132759 -1.18 0.120774 38 -0.02258 -0.2007 0.420726 39 0.120801 1.0737 0.143113 40 -0.008534 -0.0758 0.469865 41 -0.038386 -0.3412 0.366934 42 -0.079943 -0.7106 0.239727 43 0.089988 0.7998 0.213103 44 -0.106673 -0.9481 0.172977 45 -0.020411 -0.1814 0.428253 46 -0.086815 -0.7716 0.221317 47 0.038695 0.3439 0.365906 48 -0.066024 -0.5868 0.279495

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/1p8ge1305827225.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/1p8ge1305827225.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/20yun1305827225.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/20yun1305827225.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/3c97s1305827225.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305827123sx501uasafitypk/3c97s1305827225.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

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by