Opdracht 6BIS - eigencijferreeks - Sophie Van Landeghem

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Tue, 12 Apr 2011 17:48:23 +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/12/t1302630361grptssb1zpkt4vv.htm/, Retrieved Tue, 12 Apr 2011 19:46:05 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

126.304 125.511 125.495 130.133 126.257 110.323 98.417 105.749 120.665 124.075 127.245 146.731 144.979 148.210 144.670 142.970 142.524 146.142 146.522 148.128 148.798 150.181 152.388 155.694 160.662 155.520 158.262 154.338 158.196 160.371 154.856 150.636 145.899 141.242 140.834 141.119 139.104 134.437 129.425 123.155 119.273 120.472 121.523 121.983 123.658 124.794 124.827 120.382 117.395 115.790 114.283 117.271 117.448 118.764 120.550 123.554 125.412 124.182 119.828 115.361 114.226 115.214 115.864 114.276 113.469 114.883 114.172 111.225 112.149 115.618 118.002 121.382 120.663

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 'George Udny Yule' @ 216.218.223.82 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.951572 8.1302 0 2 0.874056 7.4679 0 3 0.79611 6.802 0 4 0.725202 6.1961 0 5 0.654471 5.5918 0 6 0.589471 5.0364 2e-06 7 0.535712 4.5771 9e-06 8 0.487732 4.1672 4.2e-05 9 0.43556 3.7214 0.000193 10 0.375588 3.209 0.00099 11 0.310024 2.6488 0.004947 12 0.245844 2.1005 0.01957 13 0.182741 1.5613 0.061385 14 0.117624 1.005 0.159112 15 0.062031 0.53 0.298862 16 0.0051 0.0436 0.482681 17 -0.047495 -0.4058 0.343041 18 -0.097011 -0.8289 0.204941 19 -0.144684 -1.2362 0.110178 20 -0.185055 -1.5811 0.059088 21 -0.226681 -1.9368 0.028322 22 -0.265862 -2.2715 0.013032 23 -0.293966 -2.5116 0.007114 24 -0.307371 -2.6262 0.005257 25 -0.310816 -2.6556 0.004857 26 -0.316005 -2.7 0.004307 27 -0.320592 -2.7391 0.003868 28 -0.330955 -2.8277 0.003024 29 -0.338525 -2.8924 0.002518 30 -0.335772 -2.8688 0.002692 31 -0.324877 -2.7757 0.003496 32 -0.311265 -2.6595 0.004807 33 -0.302292 -2.5828 0.005902 34 -0.304388 -2.6007 0.005628 35 -0.314942 -2.6909 0.004415 36 -0.325485 -2.7809 0.003446 37 -0.327465 -2.7979 0.003287 38 -0.322638 -2.7566 0.003686 39 -0.312836 -2.6729 0.004636 40 -0.292459 -2.4988 0.007356 41 -0.265247 -2.2663 0.0132 42 -0.234444 -2.0031 0.02444 43 -0.208192 -1.7788 0.039719 44 -0.187842 -1.6049 0.056415 45 -0.17457 -1.4915 0.070066 46 -0.167204 -1.4286 0.078693 47 -0.156274 -1.3352 0.092979 48 -0.146207 -1.2492 0.107793 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.951572 8.1302 0 2 -0.332581 -2.8416 0.002908 3 0.050458 0.4311 0.333828 4 0.011244 0.0961 0.461866 5 -0.082231 -0.7026 0.242276 6 0.044168 0.3774 0.353496 7 0.050457 0.4311 0.333833 8 -0.038348 -0.3276 0.37206 9 -0.087478 -0.7474 0.228608 10 -0.083335 -0.712 0.239362 11 -0.07156 -0.6114 0.271414 12 -0.008074 -0.069 0.472597 13 -0.050662 -0.4329 0.333196 14 -0.080512 -0.6879 0.24685 15 0.070834 0.6052 0.27346 16 -0.167266 -1.4291 0.078617 17 0.029562 0.2526 0.400654 18 -0.032894 -0.281 0.389735 19 -0.066626 -0.5693 0.285467 20 0.054615 0.4666 0.321078 21 -0.125279 -1.0704 0.143986 22 0.001845 0.0158 0.493732 23 0.074205 0.634 0.26403 24 0.036482 0.3117 0.378076 25 0.01603 0.137 0.445718 26 -0.069217 -0.5914 0.278042 27 -0.004782 -0.0409 0.48376 28 -0.134476 -1.149 0.12716 29 0.097163 0.8302 0.204578 30 0.047899 0.4093 0.341776 31 0.02166 0.1851 0.426848 32 -0.035627 -0.3044 0.380846 33 -0.144969 -1.2386 0.109727 34 -0.104046 -0.889 0.188469 35 -0.107816 -0.9212 0.179994 36 0.051234 0.4377 0.331433 37 0.069143 0.5908 0.278253 38 -0.028208 -0.241 0.405113 39 -0.011367 -0.0971 0.461449 40 0.006863 0.0586 0.476699 41 0.033355 0.285 0.388231 42 0.007458 0.0637 0.474684 43 0.014879 0.1271 0.449594 44 -0.038617 -0.3299 0.371193 45 -0.098684 -0.8432 0.200947 46 -0.006943 -0.0593 0.476429 47 0.057658 0.4926 0.311876 48 -0.033495 -0.2862 0.387774

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/1k7lm1302630500.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/1k7lm1302630500.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/2hua11302630500.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/2hua11302630500.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/3g1nm1302630500.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/12/t1302630361grptssb1zpkt4vv/3g1nm1302630500.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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