ACF met: d=0, D=0, lambda=1

*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: Sat, 19 Dec 2009 04:26:01 -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/19/t1261222004enc3fhuudnjcu6y.htm/, Retrieved Sat, 19 Dec 2009 12:26:46 +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/19/t1261222004enc3fhuudnjcu6y.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 «

441 449 452 462 455 461 461 463 462 456 455 456 472 472 471 465 459 465 468 467 463 460 462 461 476 476 471 453 443 442 444 438 427 424 416 406 431 434 418 412 404 409 412 406 398 397 385 390 413 413 401 397 397 409 419 424 428 430 424 433 456

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 0.939502 7.3377 0 2 0.868119 6.7802 0 3 0.825505 6.4474 0 4 0.799813 6.2467 0 5 0.78541 6.1342 0 6 0.750111 5.8586 0 7 0.675882 5.2788 1e-06 8 0.583499 4.5573 1.3e-05 9 0.510936 3.9905 9e-05 10 0.465947 3.6392 0.000282 11 0.452439 3.5337 0.000394 12 0.407766 3.1848 0.001141 13 0.294251 2.2982 0.012497 14 0.19285 1.5062 0.068588 15 0.121728 0.9507 0.172748 16 0.067934 0.5306 0.298818 17 0.032387 0.2529 0.400579 18 -0.016015 -0.1251 0.450434 19 -0.08854 -0.6915 0.245932 20 -0.17316 -1.3524 0.090616 21 -0.231029 -1.8044 0.038053 22 -0.263215 -2.0558 0.022046 23 -0.272475 -2.1281 0.018689 24 -0.307303 -2.4001 0.009729 25 -0.375366 -2.9317 0.00237 26 -0.421862 -3.2948 0.000822 27 -0.44511 -3.4764 0.000471 28 -0.447572 -3.4956 0.000444 29 -0.432026 -3.3742 0.000646 30 -0.422195 -3.2974 0.000815 31 -0.425574 -3.3238 0.000753 32 -0.433714 -3.3874 0.00062 33 -0.417438 -3.2603 0.000911 34 -0.387171 -3.0239 0.001824 35 -0.357359 -2.7911 0.003502 36 -0.33891 -2.647 0.00516 37 -0.342393 -2.6742 0.0048 38 -0.335605 -2.6212 0.005524 39 -0.319224 -2.4932 0.007694 40 -0.290824 -2.2714 0.013331 41 -0.25981 -2.0292 0.023405 42 -0.233414 -1.823 0.036601 43 -0.217008 -1.6949 0.047599 44 -0.201074 -1.5704 0.060743 45 -0.173089 -1.3519 0.090705 46 -0.144965 -1.1322 0.130988 47 -0.119365 -0.9323 0.177437 48 -0.09991 -0.7803 0.219109 49 -0.091255 -0.7127 0.239366 50 -0.073712 -0.5757 0.283466 51 -0.054369 -0.4246 0.336298 52 -0.03434 -0.2682 0.394723 53 -0.020725 -0.1619 0.435972 54 -0.011636 -0.0909 0.463943 55 -0.006504 -0.0508 0.479825 56 -0.003037 -0.0237 0.490578 57 0.00455 0.0355 0.485885 58 0.003818 0.0298 0.488155 59 0.0045 0.0351 0.48604 60 0.001349 0.0105 0.495815 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.939502 7.3377 0 2 -0.123964 -0.9682 0.168387 3 0.218674 1.7079 0.04637 4 0.075996 0.5936 0.277504 5 0.1221 0.9536 0.172017 6 -0.166059 -1.297 0.099764 7 -0.282051 -2.2029 0.015695 8 -0.239013 -1.8668 0.033372 9 -0.022069 -0.1724 0.431861 10 0.042039 0.3283 0.371891 11 0.289238 2.259 0.013734 12 -0.194093 -1.5159 0.067354 13 -0.488952 -3.8188 0.000158 14 0.055418 0.4328 0.333333 15 0.019358 0.1512 0.440161 16 -0.066189 -0.517 0.30353 17 0.053541 0.4182 0.338647 18 0.04456 0.348 0.364509 19 0.131254 1.0251 0.154677 20 -0.13494 -1.0539 0.148039 21 -0.030032 -0.2346 0.40767 22 -0.190775 -1.49 0.070688 23 0.005397 0.0422 0.483258 24 0.038772 0.3028 0.381528 25 0.041155 0.3214 0.374491 26 0.048999 0.3827 0.351638 27 0.071044 0.5549 0.290505 28 0.059709 0.4663 0.321317 29 0.016845 0.1316 0.447881 30 -0.024379 -0.1904 0.424813 31 0.110942 0.8665 0.194809 32 -0.026513 -0.2071 0.41832 33 0.057254 0.4472 0.32817 34 -0.133927 -1.046 0.149843 35 -0.21504 -1.6795 0.049083 36 0.094939 0.7415 0.230618 37 -0.10924 -0.8532 0.198446 38 -0.084831 -0.6625 0.255057 39 -0.020679 -0.1615 0.436113 40 0.017175 0.1341 0.446867 41 -0.004191 -0.0327 0.486998 42 -0.026803 -0.2093 0.41744 43 0.019292 0.1507 0.440366 44 0.056798 0.4436 0.329449 45 -0.04939 -0.3857 0.350513 46 0.060776 0.4747 0.318356 47 -0.05576 -0.4355 0.332368 48 -0.049814 -0.3891 0.349293 49 0.05098 0.3982 0.345949 50 0.065178 0.5091 0.306275 51 -0.062331 -0.4868 0.314064 52 -0.032517 -0.254 0.40019 53 -0.047685 -0.3724 0.35543 54 -0.01994 -0.1557 0.438377 55 -0.069459 -0.5425 0.294728 56 0.020458 0.1598 0.43679 57 -0.016272 -0.1271 0.449644 58 0.078577 0.6137 0.270845 59 0.070146 0.5479 0.292894 60 -0.051255 -0.4003 0.345161

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/19/t1261222004enc3fhuudnjcu6y/1gp7b1261221959.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/19/t1261222004enc3fhuudnjcu6y/1gp7b1261221959.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/19/t1261222004enc3fhuudnjcu6y/2v2ni1261221959.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/19/t1261222004enc3fhuudnjcu6y/2v2ni1261221959.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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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