Opgave 6 BIS: Eigen reeks, Stap 2

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Mon, 09 May 2011 14:43:27 +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/09/t1304952021k25hctj45cymdl1.htm/, Retrieved Mon, 09 May 2011 16:40:21 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

190.2 180.7 193.6 192.8 195.5 197.2 196.9 178.9 172.4 156.4 143.7 153.6 168.8 185.8 199.9 205.4 197.5 199.6 200.5 193.7 179.6 169.1 169.8 195.5 194.8 204.5 203.8 204.8 204.9 240 248.3 258.4 254.9 288.3 333.6 346.3 357.5 490.7 468.2 471.2 517.1 609.2 682 614 554.2 406.8 348.6 298.8 313.7 282.1 232.9 239.3 241.9 265.7 276 271.5 254.6 269.9 293.5 306.1 365.4 347.9 352.1 377.9 377.4 372.2 362.5 341.9 354.8 369.2 406.7 454.7

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.377365 3.1797 0.001093 2 0.1837 1.5479 0.063048 3 -0.008695 -0.0733 0.470901 4 0.004532 0.0382 0.484823 5 0.048519 0.4088 0.341947 6 -0.035893 -0.3024 0.381602 7 -0.019928 -0.1679 0.433563 8 -0.233139 -1.9645 0.026696 9 -0.205224 -1.7293 0.044055 10 -0.179614 -1.5135 0.067302 11 0.029442 0.2481 0.402393 12 -0.037082 -0.3125 0.377803 13 -0.182453 -1.5374 0.064324 14 -0.135864 -1.1448 0.128067 15 -0.186314 -1.5699 0.060441 16 -0.081832 -0.6895 0.24637 17 -0.003686 -0.0311 0.487655 18 0.050906 0.4289 0.334634 19 0.026082 0.2198 0.413339 20 -0.032401 -0.273 0.392818 21 -0.030466 -0.2567 0.399072 22 -0.003636 -0.0306 0.487824 23 0.100505 0.8469 0.199957 24 -0.053509 -0.4509 0.326728 25 -0.088318 -0.7442 0.229611 26 -0.052838 -0.4452 0.328758 27 -0.050064 -0.4218 0.337206 28 0.011243 0.0947 0.462396 29 0.118756 1.0007 0.160196 30 0.009805 0.0826 0.467194 31 -0.005009 -0.0422 0.483227 32 -0.098151 -0.827 0.205494 33 -0.047717 -0.4021 0.34442 34 0.040388 0.3403 0.367312 35 0.051121 0.4308 0.333975 36 0.044325 0.3735 0.35495 37 0.079175 0.6671 0.253423 38 0.040869 0.3444 0.365792 39 0.023991 0.2022 0.420188 40 0.044124 0.3718 0.355575 41 0.013305 0.1121 0.455527 42 0.030264 0.255 0.399728 43 -0.003559 -0.03 0.488079 44 0.001087 0.0092 0.49636 45 0.016437 0.1385 0.445118 46 0.032178 0.2711 0.393538 47 0.014414 0.1215 0.451839 48 0.012069 0.1017 0.459644 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.377365 3.1797 0.001093 2 0.048153 0.4057 0.343076 3 -0.108519 -0.9144 0.181802 4 0.038609 0.3253 0.372945 5 0.065769 0.5542 0.290598 6 -0.098311 -0.8284 0.205115 7 0.00981 0.0827 0.467179 8 -0.239969 -2.022 0.023472 9 -0.064548 -0.5439 0.294111 10 -0.035326 -0.2977 0.383414 11 0.138149 1.1641 0.124147 12 -0.119018 -1.0029 0.159666 13 -0.191081 -1.6101 0.055909 14 0.007955 0.067 0.473374 15 -0.111661 -0.9409 0.174981 16 -0.072171 -0.6081 0.272523 17 0.049558 0.4176 0.338755 18 -0.026962 -0.2272 0.410467 19 -0.005727 -0.0483 0.480825 20 -0.033097 -0.2789 0.390574 21 -0.089014 -0.75 0.227853 22 -0.067216 -0.5664 0.286465 23 0.052155 0.4395 0.33083 24 -0.177388 -1.4947 0.069712 25 -0.123769 -1.0429 0.150268 26 0.051675 0.4354 0.332289 27 -0.057867 -0.4876 0.313669 28 -0.085336 -0.7191 0.237233 29 0.139014 1.1713 0.122687 30 -0.208655 -1.7582 0.041515 31 -0.019288 -0.1625 0.435677 32 -0.092472 -0.7792 0.219231 33 -0.098379 -0.829 0.204953 34 -0.039029 -0.3289 0.371612 35 0.040722 0.3431 0.366259 36 -0.059227 -0.4991 0.309642 37 0.046868 0.3949 0.347044 38 -0.059905 -0.5048 0.307643 39 -0.043963 -0.3704 0.356079 40 -0.159644 -1.3452 0.091423 41 -0.019064 -0.1606 0.436417 42 -0.008564 -0.0722 0.471338 43 -0.052263 -0.4404 0.3305 44 0.039678 0.3343 0.369556 45 -0.020984 -0.1768 0.430079 46 -0.090093 -0.7591 0.225141 47 0.017143 0.1445 0.442777 48 -0.086697 -0.7305 0.233737

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/1n21t1304952204.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/1n21t1304952204.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/2q57e1304952204.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/2q57e1304952204.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/3zuuq1304952204.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304952021k25hctj45cymdl1/3zuuq1304952204.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