marina cabraja: opgave 6bis: koffie, thee en cacao: autocorrelatie

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Sun, 03 Apr 2011 16:11:32 +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/03/t13018469967o9nz4c24l3i7fa.htm/, Retrieved Sun, 03 Apr 2011 18:09:59 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

106,42 106,22 106,32 105,81 105,92 107,54 107,34 107,24 107,74 105,71 105,41 106,22 106,32 106,12 106,22 105,92 105,71 105,71 105,92 105,71 105,41 104,49 101,35 99,72 99,01 97,89 95,86 94,95 95,35 95,15 95,46 95,56 95,05 94,64 93,63 93,12 93,53 97,18 96,27 95,15 97,08 101,95 103,07 103,68 102,87 102,56 103,38 103,27 102,89 102,69 101,54 102,9 101,53 101,96 101,99 101,11 101,75 101,71 104,11 103,57 103,32 103,64 103,68 103,79 103,01 101,54 101,9 103,68 104,62 104,11 105,04 104,83 105,05 104,68 107,32 109,9 109,77 110,69 110,54 110,89 110,95 109,73 110,85 110,39 110,58 110,4 111,07 110,86 111,38 111,44 110,36 110,06 108,34 107,94 107,39 107,1 107,61 107,74 106,9 106,71 106,6 108,21 110,54 110,91 109,51 110,27 111,39 112,13 111,64

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' @ www.wessa.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.964268 10.0673 0 2 0.915689 9.5601 0 3 0.870502 9.0883 0 4 0.827883 8.6434 0 5 0.77941 8.1373 0 6 0.717031 7.486 0 7 0.656125 6.8501 0 8 0.602218 6.2873 0 9 0.555297 5.7975 0 10 0.510515 5.3299 0 11 0.465498 4.8599 2e-06 12 0.422001 4.4058 1.2e-05 13 0.376353 3.9292 7.5e-05 14 0.332038 3.4666 0.000378 15 0.29045 3.0324 0.001516 16 0.260091 2.7154 0.003849 17 0.227554 2.3757 0.00963 18 0.18812 1.964 0.026037 19 0.156572 1.6347 0.052503 20 0.128866 1.3454 0.090645 21 0.107812 1.1256 0.131405 22 0.085446 0.8921 0.187157 23 0.06866 0.7168 0.237506 24 0.05746 0.5999 0.274909 25 0.050408 0.5263 0.299882 26 0.046021 0.4805 0.315927 27 0.033132 0.3459 0.365038 28 0.020062 0.2095 0.417242 29 0.003677 0.0384 0.484725 30 -0.015065 -0.1573 0.437656 31 -0.03705 -0.3868 0.349823 32 -0.061559 -0.6427 0.260885 33 -0.081288 -0.8487 0.198962 34 -0.108189 -1.1295 0.130577 35 -0.129563 -1.3527 0.08948 36 -0.147653 -1.5415 0.063042 37 -0.164274 -1.7151 0.044587 38 -0.183961 -1.9206 0.028697 39 -0.208232 -2.174 0.015934 40 -0.231231 -2.4141 0.00872 41 -0.256343 -2.6763 0.004297 42 -0.279313 -2.9161 0.002152 43 -0.296936 -3.1001 0.001231 44 -0.316581 -3.3052 0.000643 45 -0.337908 -3.5279 0.000307 46 -0.361505 -3.7742 0.000131 47 -0.384412 -4.0134 5.5e-05 48 -0.40603 -4.2391 2.4e-05 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.964268 10.0673 0 2 -0.201247 -2.1011 0.01897 3 0.057806 0.6035 0.273711 4 -0.010652 -0.1112 0.455828 5 -0.116243 -1.2136 0.113759 6 -0.199547 -2.0833 0.01978 7 0.045549 0.4755 0.317674 8 0.024793 0.2588 0.398121 9 0.042831 0.4472 0.327819 10 0.009018 0.0942 0.462581 11 -0.002612 -0.0273 0.489149 12 -0.03262 -0.3406 0.367046 13 -0.105702 -1.1036 0.136107 14 -0.022209 -0.2319 0.408537 15 -0.002105 -0.022 0.491254 16 0.1419 1.4815 0.070682 17 -0.103958 -1.0854 0.14008 18 -0.074242 -0.7751 0.219977 19 0.114526 1.1957 0.117206 20 -0.06713 -0.7009 0.242443 21 0.017456 0.1822 0.427863 22 -0.017215 -0.1797 0.428848 23 0.124487 1.2997 0.098226 24 -0.01693 -0.1768 0.430015 25 0.025689 0.2682 0.394524 26 -0.006702 -0.07 0.472173 27 -0.145619 -1.5203 0.065665 28 -0.018351 -0.1916 0.42421 29 -0.09841 -1.0274 0.153245 30 -0.015401 -0.1608 0.436278 31 -0.029411 -0.3071 0.379692 32 -0.002296 -0.024 0.49046 33 0.029541 0.3084 0.379175 34 -0.113121 -1.181 0.120083 35 0.092659 0.9674 0.167747 36 -0.047382 -0.4947 0.310911 37 -0.010718 -0.1119 0.455555 38 -0.087843 -0.9171 0.180557 39 -0.019893 -0.2077 0.417928 40 -0.058725 -0.6131 0.27054 41 -0.068957 -0.7199 0.236554 42 -0.010823 -0.113 0.455121 43 0.108349 1.1312 0.130228 44 -0.064257 -0.6709 0.251864 45 -0.079411 -0.8291 0.204437 46 -0.029204 -0.3049 0.380512 47 -0.085847 -0.8963 0.186043 48 -0.030681 -0.3203 0.37467

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/1jw5x1301847090.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/1jw5x1301847090.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/29xve1301847090.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/29xve1301847090.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/32do31301847090.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018469967o9nz4c24l3i7fa/32do31301847090.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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