*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: Thu, 17 Dec 2009 03:05:30 -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/17/t1261044697jtdhfjn123ypmyv.htm/, Retrieved Thu, 17 Dec 2009 11:11:39 +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/17/t1261044697jtdhfjn123ypmyv.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 «

9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8 8.2 8.1 8.1 8 7.9 7.9 8 8 7.9 8 7.7 7.2 7.5 7.3 7 7 7 7.2 7.3 7.1 6.8 6.4 6.1 6.5 7.7 7.9 7.5 6.9 6.6 6.9 7.7 8 8 7.7 7.3 7.4 8.1 8.3 8.2

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 'Gwilym Jenkins' @ 72.249.127.135 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.84266 6.5814 0 2 0.636226 4.9691 3e-06 3 0.529187 4.1331 5.5e-05 4 0.548333 4.2826 3.3e-05 5 0.638853 4.9896 3e-06 6 0.683904 5.3415 1e-06 7 0.604917 4.7245 7e-06 8 0.459583 3.5895 0.000331 9 0.338687 2.6452 0.005184 10 0.317357 2.4786 0.007985 11 0.336308 2.6267 0.005444 12 0.346642 2.7074 0.004393 13 0.262432 2.0497 0.022352 14 0.164205 1.2825 0.102262 15 0.092037 0.7188 0.237494 16 0.048062 0.3754 0.354343 17 0.017024 0.133 0.447331 18 -0.019578 -0.1529 0.439486 19 -0.080082 -0.6255 0.267002 20 -0.146691 -1.1457 0.128198 21 -0.193526 -1.5115 0.067914 22 -0.209451 -1.6359 0.053509 23 -0.220702 -1.7237 0.044911 24 -0.237888 -1.858 0.034001 25 -0.294984 -2.3039 0.012325 26 -0.326906 -2.5532 0.006595 27 -0.322331 -2.5175 0.007231 28 -0.299247 -2.3372 0.011364 29 -0.285495 -2.2298 0.014727 30 -0.294924 -2.3034 0.012339 31 -0.328809 -2.5681 0.006346 32 -0.378508 -2.9562 0.002212 33 -0.38453 -3.0033 0.001935 34 -0.324054 -2.5309 0.006985 35 -0.280647 -2.1919 0.016106 36 -0.268344 -2.0958 0.020127 37 -0.296317 -2.3143 0.012017 38 -0.318896 -2.4907 0.007744 39 -0.300304 -2.3455 0.011136 40 -0.245398 -1.9166 0.029987 41 -0.191198 -1.4933 0.070256 42 -0.167201 -1.3059 0.098248 43 -0.19103 -1.492 0.070427 44 -0.211452 -1.6515 0.051888 45 -0.170221 -1.3295 0.094323 46 -0.085117 -0.6648 0.254346 47 -0.046184 -0.3607 0.359781 48 -0.050928 -0.3978 0.346098 49 -0.085879 -0.6707 0.252459 50 -0.100354 -0.7838 0.218098 51 -0.070976 -0.5543 0.290687 52 -0.014283 -0.1116 0.455771 53 0.012596 0.0984 0.460977 54 0.015038 0.1175 0.453445 55 -0.006422 -0.0502 0.480081 56 -0.023932 -0.1869 0.426173 57 -0.004603 -0.036 0.485719 58 0.031082 0.2428 0.404503 59 0.034066 0.2661 0.395543 60 0.018194 0.1421 0.443734 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.84266 6.5814 0 2 -0.254719 -1.9894 0.025572 3 0.262423 2.0496 0.022356 4 0.280867 2.1936 0.016041 5 0.269342 2.1036 0.019771 6 0.051683 0.4037 0.343939 7 -0.161316 -1.2599 0.106249 8 -0.116504 -0.9099 0.183222 9 -0.127042 -0.9922 0.162503 10 0.018476 0.1443 0.44287 11 -0.146335 -1.1429 0.12877 12 0.015751 0.123 0.451247 13 -0.232271 -1.8141 0.037291 14 0.135396 1.0575 0.147232 15 -0.069247 -0.5408 0.295294 16 -0.084446 -0.6595 0.256015 17 -0.10991 -0.8584 0.197009 18 -0.054208 -0.4234 0.336754 19 -0.028882 -0.2256 0.411142 20 -0.088359 -0.6901 0.246371 21 0.027134 0.2119 0.416438 22 -0.032114 -0.2508 0.401399 23 0.086306 0.6741 0.251407 24 -0.010248 -0.08 0.468235 25 -0.067692 -0.5287 0.299468 26 0.092004 0.7186 0.237574 27 0.031145 0.2433 0.404313 28 0.067524 0.5274 0.299923 29 -0.03224 -0.2518 0.401019 30 0.019739 0.1542 0.438994 31 -0.054176 -0.4231 0.336846 32 -0.152247 -1.1891 0.119506 33 0.014817 0.1157 0.454126 34 0.039455 0.3082 0.379507 35 -0.081312 -0.6351 0.263879 36 -0.009829 -0.0768 0.469529 37 -0.006445 -0.0503 0.48001 38 0.006844 0.0535 0.478772 39 0.019578 0.1529 0.439489 40 0.007227 0.0564 0.477587 41 -0.023844 -0.1862 0.426441 42 -0.000647 -0.0051 0.497993 43 -0.094823 -0.7406 0.230891 44 0.046742 0.3651 0.358163 45 0.116963 0.9135 0.182285 46 0.03407 0.2661 0.395533 47 -0.06712 -0.5242 0.30101 48 0.006091 0.0476 0.481106 49 -0.039081 -0.3052 0.380614 50 -0.038195 -0.2983 0.383239 51 -0.063053 -0.4925 0.31208 52 -0.051551 -0.4026 0.344315 53 -0.074723 -0.5836 0.280818 54 0.064463 0.5035 0.308222 55 -0.027433 -0.2143 0.415531 56 -0.021294 -0.1663 0.434231 57 -0.002518 -0.0197 0.492186 58 -0.051387 -0.4013 0.344785 59 0.006943 0.0542 0.478467 60 -0.062739 -0.49 0.312943

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/17/t1261044697jtdhfjn123ypmyv/17kek1261044327.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/17/t1261044697jtdhfjn123ypmyv/17kek1261044327.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/17/t1261044697jtdhfjn123ypmyv/29iq41261044327.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/17/t1261044697jtdhfjn123ypmyv/29iq41261044327.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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