Opgave 6bis-Daphné Van den Buys

*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, 11 Apr 2011 20:51:27 +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/Apr/11/t1302555032cflys0fpmmbsem6.htm/, Retrieved Mon, 11 Apr 2011 22:50:35 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516

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 'Herman Ole Andreas Wold' @ www.yougetit.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.243059 2.2144 0.014772 2 -0.193211 -1.7602 0.041026 3 -0.296378 -2.7001 0.004199 4 -0.258613 -2.3561 0.010413 5 0.073346 0.6682 0.252924 6 0.189534 1.7267 0.043967 7 0.042953 0.3913 0.34828 8 -0.238333 -2.1713 0.016381 9 -0.25998 -2.3685 0.010091 10 -0.157491 -1.4348 0.077549 11 0.255609 2.3287 0.011153 12 0.792132 7.2167 0 13 0.177096 1.6134 0.055224 14 -0.163074 -1.4857 0.070577 15 -0.280874 -2.5589 0.006158 16 -0.229544 -2.0912 0.019782 17 0.070022 0.6379 0.262636 18 0.123004 1.1206 0.132841 19 0.033712 0.3071 0.379758 20 -0.224087 -2.0415 0.022187 21 -0.234603 -2.1373 0.017757 22 -0.096076 -0.8753 0.191971 23 0.195489 1.781 0.039286 24 0.599648 5.4631 0 25 0.147367 1.3426 0.091535 26 -0.155905 -1.4204 0.079624 27 -0.246967 -2.25 0.013548 28 -0.190847 -1.7387 0.042898 29 0.03887 0.3541 0.362073 30 0.0701 0.6386 0.262409 31 0.016655 0.1517 0.439882 32 -0.189232 -1.724 0.044217 33 -0.159179 -1.4502 0.075386 34 -0.071682 -0.6531 0.257762 35 0.139388 1.2699 0.103837 36 0.489822 4.4625 1.3e-05 37 0.098682 0.899 0.185618 38 -0.16148 -1.4712 0.072515 39 -0.241118 -2.1967 0.015416 40 -0.141991 -1.2936 0.099696 41 0.035321 0.3218 0.374212 42 0.075425 0.6872 0.246951 43 0.002587 0.0236 0.490626 44 -0.162288 -1.4785 0.071527 45 -0.11103 -1.0115 0.157351 46 -0.059516 -0.5422 0.294561 47 0.092825 0.8457 0.200083 48 0.373614 3.4038 0.000513 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.243059 2.2144 0.014772 2 -0.268129 -2.4428 0.008348 3 -0.196563 -1.7908 0.038488 4 -0.208691 -1.9013 0.030368 5 0.096544 0.8796 0.19082 6 0.01001 0.0912 0.463779 7 -0.083118 -0.7572 0.225525 8 -0.264074 -2.4058 0.009179 9 -0.12893 -1.1746 0.121754 10 -0.198987 -1.8129 0.036734 11 0.183515 1.6719 0.049155 12 0.695833 6.3393 0 13 -0.107502 -0.9794 0.165116 14 0.141152 1.286 0.101018 15 0.036331 0.331 0.370742 16 0.063952 0.5826 0.280861 17 -0.067935 -0.6189 0.268833 18 -0.123399 -1.1242 0.13208 19 0.060447 0.5507 0.29166 20 -0.102966 -0.9381 0.175467 21 -0.028707 -0.2615 0.397166 22 0.040995 0.3735 0.354871 23 -0.193374 -1.7617 0.040899 24 -0.024854 -0.2264 0.41071 25 -0.003022 -0.0275 0.489051 26 -0.094805 -0.8637 0.195116 27 0.008309 0.0757 0.46992 28 -0.037071 -0.3377 0.368208 29 -0.022738 -0.2072 0.418199 30 -0.053732 -0.4895 0.312883 31 -0.052418 -0.4776 0.317112 32 0.07124 0.649 0.259057 33 0.032999 0.3006 0.382222 34 -0.071823 -0.6543 0.257351 35 0.057525 0.5241 0.30081 36 0.068983 0.6285 0.265712 37 -0.076644 -0.6983 0.243485 38 -0.055276 -0.5036 0.307942 39 -0.122366 -1.1148 0.134075 40 0.102055 0.9298 0.177594 41 -0.092757 -0.8451 0.200255 42 0.097581 0.889 0.188285 43 -0.032514 -0.2962 0.383903 44 -0.037066 -0.3377 0.368226 45 0.023069 0.2102 0.417027 46 -0.040332 -0.3674 0.357111 47 -0.115008 -1.0478 0.148893 48 -0.075615 -0.6889 0.246409

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/1zev61302555086.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/1zev61302555086.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/2te8d1302555086.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/2te8d1302555086.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/31ng41302555086.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302555032cflys0fpmmbsem6/31ng41302555086.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 2 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 2 ; 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')

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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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