Opdracht6bis: autocorrelatie (eigen reeks) - Yesse De Ley

*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 21:16:33 +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/t1302556444x2ddr84jz0pcamp.htm/, Retrieved Mon, 11 Apr 2011 23:14:08 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

101397 97994 94044 91159 87239 89235 118647 125620 125154 117529 109459 108483 107137 104699 100804 96066 91971 93228 120144 127233 127166 118194 109940 106683 102834 99882 96666 92540 88744 89321 115870 122401 122030 113802 105791 103076 98658 96945 92497 90687 88796 90015 113228 118711 117460 106556 97347 92657 93118 89037 83570 81693 75956 73993 97088 102394 96549 89727 82336 82653 82303 79596 74472 73562 66618 69029 89899 93774 90305 83799 80320 82497 84420 84646 84186 83269 77793 81145 101691 107357 104253 95963 91432 94324 93855 92183 87600 83641 78195 79604 100846 105293 102518 93132 87479 85476

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 'Herman Ole Andreas Wold' @ www.yougetit.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.820641 8.0406 0 2 0.524967 5.1436 1e-06 3 0.291089 2.8521 0.002659 4 0.189468 1.8564 0.033232 5 0.19243 1.8854 0.031199 6 0.205628 2.0147 0.023365 7 0.18223 1.7855 0.038671 8 0.158623 1.5542 0.061715 9 0.21987 2.1543 0.016861 10 0.389792 3.8192 0.000119 11 0.616092 6.0364 0 12 0.739653 7.2471 0 13 0.569536 5.5803 0 14 0.300749 2.9467 0.002015 15 0.088797 0.87 0.193226 16 -0.005387 -0.0528 0.479009 17 -0.007811 -0.0765 0.469578 18 -0.001716 -0.0168 0.493311 19 -0.025082 -0.2458 0.4032 20 -0.04541 -0.4449 0.328687 21 0.00861 0.0844 0.466473 22 0.152028 1.4896 0.069809 23 0.338699 3.3186 0.00064 24 0.437135 4.283 2.2e-05 25 0.287504 2.817 0.002943 26 0.060295 0.5908 0.278032 27 -0.114188 -1.1188 0.133007 28 -0.185626 -1.8188 0.036033 29 -0.180697 -1.7705 0.039913 30 -0.171124 -1.6767 0.048431 31 -0.191529 -1.8766 0.031805 32 -0.210273 -2.0602 0.021041 33 -0.161964 -1.5869 0.05791 34 -0.043227 -0.4235 0.336424 35 0.111271 1.0902 0.139172 36 0.18751 1.8372 0.034636 37 0.060893 0.5966 0.276079 38 -0.125255 -1.2272 0.111366 39 -0.258324 -2.531 0.006499 40 -0.303622 -2.9749 0.001854 41 -0.289716 -2.8386 0.002765 42 -0.278834 -2.732 0.003747 43 -0.303437 -2.9731 0.001864 44 -0.322527 -3.1601 0.001055 45 -0.284139 -2.784 0.003234 46 -0.184068 -1.8035 0.037224 47 -0.052965 -0.519 0.302495 48 0.018875 0.1849 0.426835 49 -0.072903 -0.7143 0.238388 50 -0.206038 -2.0188 0.023151 51 -0.290717 -2.8484 0.002688 52 -0.3035 -2.9737 0.00186 53 -0.273978 -2.6844 0.00428 54 -0.251127 -2.4605 0.00783 55 -0.256672 -2.5149 0.006785 56 -0.260453 -2.5519 0.006146 57 -0.220852 -2.1639 0.016477 58 -0.137249 -1.3448 0.090936 59 -0.029279 -0.2869 0.387412 60 0.027491 0.2694 0.394115 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.820641 8.0406 0 2 -0.454711 -4.4552 1.1e-05 3 0.144926 1.42 0.079427 4 0.131656 1.29 0.100082 5 0.076166 0.7463 0.228664 6 -0.06543 -0.6411 0.261498 7 -0.003673 -0.036 0.485684 8 0.121834 1.1937 0.117764 9 0.291224 2.8534 0.002649 10 0.303698 2.9756 0.00185 11 0.357857 3.5063 0.000346 12 0.039944 0.3914 0.348195 13 -0.656723 -6.4345 0 14 0.217388 2.13 0.017866 15 -0.057834 -0.5667 0.286136 16 -0.168087 -1.6469 0.051423 17 -0.10358 -1.0149 0.156358 18 -0.044454 -0.4356 0.332068 19 0.00374 0.0366 0.485421 20 -0.007556 -0.074 0.47057 21 -0.013192 -0.1293 0.448712 22 -0.011051 -0.1083 0.457 23 -0.037508 -0.3675 0.357026 24 0.066835 0.6548 0.257066 25 -0.093156 -0.9127 0.181832 26 0.079605 0.78 0.218666 27 -0.02383 -0.2335 0.407942 28 -0.018393 -0.1802 0.428681 29 -0.014632 -0.1434 0.443151 30 -0.002527 -0.0248 0.49015 31 -0.066897 -0.6555 0.256872 32 -0.036069 -0.3534 0.362281 33 -0.007718 -0.0756 0.46994 34 -0.083527 -0.8184 0.207578 35 -0.015061 -0.1476 0.441499 36 -0.052419 -0.5136 0.304358 37 0.021732 0.2129 0.415915 38 -0.028363 -0.2779 0.390842 39 0.026197 0.2567 0.398989 40 -0.031708 -0.3107 0.378361 41 -0.026069 -0.2554 0.399471 42 -0.017955 -0.1759 0.430364 43 -0.073506 -0.7202 0.236572 44 0.024042 0.2356 0.407136 45 -0.09616 -0.9422 0.174235 46 0.00918 0.0899 0.464261 47 -0.027367 -0.2681 0.394582 48 0.059211 0.5801 0.281588 49 -0.001406 -0.0138 0.494518 50 0.041981 0.4113 0.340875 51 0.013654 0.1338 0.446927 52 0.031259 0.3063 0.380028 53 0.01463 0.1433 0.443158 54 0.070093 0.6868 0.246941 55 0.099728 0.9771 0.165481 56 -0.044642 -0.4374 0.331402 57 0.005675 0.0556 0.477887 58 0.006297 0.0617 0.475466 59 -0.007313 -0.0717 0.471514 60 -0.073189 -0.7171 0.237525

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/12u901302556591.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/12u901302556591.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/2t6qb1302556591.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/2t6qb1302556591.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/3l3df1302556591.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t1302556444x2ddr84jz0pcamp/3l3df1302556591.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 (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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