opgave 6 bis oefening 1

*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 10:58:24 +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/t1305802612hwito8ra9lby3g3.htm/, Retrieved Thu, 19 May 2011 12:56:55 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032 17696 17745 19394 20148 20108 18584 18441 18391 19178 18079 18483 19644 19195 19650 20830 23595 22937 21814 21928 21777 21383 21467 22052 22680 24320 24977 25204 25739 26434 27525 30695 32436 30160 30236 31293 31077 32226 33865 32810

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 3 seconds R Server 'Gwilym Jenkins' @ www.wessa.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.941025 8.0401 0 2 0.873138 7.4601 0 3 0.815843 6.9706 0 4 0.760515 6.4978 0 5 0.701632 5.9947 0 6 0.651 5.5621 0 7 0.596768 5.0988 1e-06 8 0.527966 4.5109 1.2e-05 9 0.470041 4.016 7.1e-05 10 0.427547 3.653 0.000242 11 0.392 3.3492 0.000642 12 0.360045 3.0762 0.001475 13 0.329246 2.8131 0.00315 14 0.297715 2.5437 0.006543 15 0.269425 2.302 0.012096 16 0.248717 2.125 0.018484 17 0.230413 1.9687 0.026395 18 0.210724 1.8004 0.037962 19 0.195484 1.6702 0.04958 20 0.177909 1.5201 0.066409 21 0.155574 1.3292 0.093956 22 0.132683 1.1336 0.130327 23 0.101643 0.8684 0.194 24 0.063605 0.5434 0.294242 25 0.039654 0.3388 0.367865 26 0.024999 0.2136 0.415732 27 0.008169 0.0698 0.472272 28 -0.013192 -0.1127 0.455285 29 -0.03005 -0.2567 0.399049 30 -0.04691 -0.4008 0.344869 31 -0.069101 -0.5904 0.278373 32 -0.088786 -0.7586 0.225272 33 -0.1054 -0.9005 0.185398 34 -0.124008 -1.0595 0.146428 35 -0.150666 -1.2873 0.10103 36 -0.177194 -1.5139 0.067178 37 -0.195188 -1.6677 0.049832 38 -0.205104 -1.7524 0.041951 39 -0.215324 -1.8397 0.034937 40 -0.227725 -1.9457 0.027772 41 -0.239429 -2.0457 0.022195 42 -0.246349 -2.1048 0.019375 43 -0.250255 -2.1382 0.017925 44 -0.259843 -2.2201 0.014758 45 -0.268773 -2.2964 0.012262 46 -0.27499 -2.3495 0.010753 47 -0.284275 -2.4289 0.008805 48 -0.293983 -2.5118 0.007112 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.941025 8.0401 0 2 -0.108232 -0.9247 0.179076 3 0.06293 0.5377 0.296218 4 -0.029086 -0.2485 0.402217 5 -0.056196 -0.4801 0.316283 6 0.045277 0.3868 0.349998 7 -0.080791 -0.6903 0.246105 8 -0.145281 -1.2413 0.109237 9 0.071246 0.6087 0.272297 10 0.057074 0.4876 0.313634 11 0.032382 0.2767 0.391407 12 0.02004 0.1712 0.432262 13 -0.032611 -0.2786 0.390659 14 -0.011892 -0.1016 0.459675 15 0.024155 0.2064 0.418533 16 0.012592 0.1076 0.457311 17 -0.018453 -0.1577 0.437578 18 -0.022058 -0.1885 0.425518 19 0.03427 0.2928 0.385253 20 -0.028664 -0.2449 0.403609 21 -0.039415 -0.3368 0.36863 22 -0.028681 -0.245 0.403553 23 -0.113302 -0.9681 0.168107 24 -0.060701 -0.5186 0.302795 25 0.111904 0.9561 0.171087 26 0.024382 0.2083 0.417781 27 -0.012029 -0.1028 0.459212 28 -0.041087 -0.351 0.363281 29 0.007321 0.0626 0.475146 30 0.000738 0.0063 0.497492 31 -0.071583 -0.6116 0.271351 32 -0.057679 -0.4928 0.311814 33 -0.022515 -0.1924 0.423995 34 -0.009237 -0.0789 0.468657 35 -0.065524 -0.5598 0.288653 36 -0.034126 -0.2916 0.38572 37 0.036137 0.3088 0.379193 38 0.042463 0.3628 0.358901 39 -0.031199 -0.2666 0.395279 40 -0.033093 -0.2828 0.389084 41 -0.015428 -0.1318 0.447747 42 0.028114 0.2402 0.405421 43 0.012504 0.1068 0.457607 44 -0.101086 -0.8637 0.195297 45 -0.025355 -0.2166 0.414551 46 0.011532 0.0985 0.46089 47 -0.049646 -0.4242 0.336342 48 -0.033035 -0.2822 0.389276

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/1y9jb1305802701.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/1y9jb1305802701.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/2n9h21305802701.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/2n9h21305802701.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/38j7q1305802701.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/19/t1305802612hwito8ra9lby3g3/38j7q1305802701.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; 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 (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

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