opgave 6 bis oef 2 stap 1- tijdreeksen- sophie berns

*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, 07 Apr 2011 15:18:31 +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/07/t1302189422ib1lw5c7drpde21.htm/, Retrieved Thu, 07 Apr 2011 17:17:05 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

41 39 50 40 43 38 44 35 39 35 29 49 50 59 63 32 39 47 53 60 57 52 70 90 74 62 55 84 94 70 108 139 120 97 126 149 158 124 140 109 114 77 120 133 110 92 97 78 99 107 112 90 98 125 155 190 236 189 174 178 136 161 171 149 184 155 276 224 213 279 268 287 238 213 257 293 212 246 353 339 308 247 257 322 298 273 312 249 286 279 309 401 309 328 353 354 327 324 285 243 241 287 355 460 364 487 452 391 500 451 375 372 302 316 398 394 431 431

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 'Gwilym Jenkins' @ www.wessa.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.927656 10.0769 0 2 0.881093 9.5711 0 3 0.853423 9.2705 0 4 0.807836 8.7753 0 5 0.796502 8.6522 0 6 0.774416 8.4123 0 7 0.749256 8.139 0 8 0.74445 8.0868 0 9 0.711673 7.7308 0 10 0.68121 7.3998 0 11 0.683985 7.43 0 12 0.668497 7.2617 0 13 0.628434 6.8265 0 14 0.599425 6.5114 0 15 0.550381 5.9787 0 16 0.519451 5.6427 0 17 0.505351 5.4895 0 18 0.483207 5.249 0 19 0.477599 5.1881 0 20 0.464527 5.0461 1e-06 21 0.434123 4.7158 3e-06 22 0.428087 4.6502 4e-06 23 0.411517 4.4702 9e-06 24 0.393606 4.2757 1.9e-05 25 0.376862 4.0938 3.9e-05 26 0.343066 3.7267 0.00015 27 0.307159 3.3366 0.000567 28 0.286313 3.1102 0.001172 29 0.260898 2.8341 0.002704 30 0.244967 2.661 0.004438 31 0.23334 2.5347 0.006281 32 0.210258 2.284 0.01208 33 0.196249 2.1318 0.017548 34 0.185795 2.0183 0.022917 35 0.172706 1.8761 0.031558 36 0.168377 1.829 0.034959 37 0.152982 1.6618 0.049603 38 0.123035 1.3365 0.091978 39 0.105298 1.1438 0.127505 40 0.062516 0.6791 0.249203 41 0.035882 0.3898 0.348703 42 0.01707 0.1854 0.426608 43 -0.012611 -0.137 0.445634 44 -0.031493 -0.3421 0.366443 45 -0.048345 -0.5252 0.30023 46 -0.062489 -0.6788 0.249296 47 -0.072099 -0.7832 0.217541 48 -0.094604 -1.0277 0.153106 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.927656 10.0769 0 2 0.147346 1.6006 0.056071 3 0.145266 1.578 0.058622 4 -0.091894 -0.9982 0.160107 5 0.21708 2.3581 0.010007 6 -0.033553 -0.3645 0.358077 7 0.031706 0.3444 0.365573 8 0.091813 0.9973 0.160319 9 -0.11603 -1.2604 0.105005 10 -0.032385 -0.3518 0.36281 11 0.188027 2.0425 0.021665 12 -0.006822 -0.0741 0.470525 13 -0.245318 -2.6648 0.004391 14 -0.024909 -0.2706 0.393592 15 -0.123749 -1.3443 0.090722 16 0.031462 0.3418 0.366569 17 0.065276 0.7091 0.239837 18 0.065421 0.7107 0.239349 19 -0.004895 -0.0532 0.478841 20 -0.017456 -0.1896 0.424968 21 -0.002401 -0.0261 0.489618 22 0.100152 1.0879 0.139421 23 -0.059625 -0.6477 0.259221 24 0.010071 0.1094 0.456537 25 -0.077704 -0.8441 0.200165 26 -0.064687 -0.7027 0.241818 27 -0.065825 -0.715 0.237996 28 0.050916 0.5531 0.290626 29 -0.030751 -0.334 0.369471 30 -0.045694 -0.4964 0.310279 31 -0.025587 -0.278 0.390768 32 0.001948 0.0212 0.491577 33 0.037362 0.4059 0.342792 34 0.045642 0.4958 0.310479 35 0.065476 0.7113 0.239166 36 -0.029606 -0.3216 0.374162 37 -0.025206 -0.2738 0.392356 38 -0.080515 -0.8746 0.191779 39 0.058311 0.6334 0.263843 40 -0.24229 -2.6319 0.004812 41 0.038259 0.4156 0.33923 42 -0.122304 -1.3286 0.093278 43 -0.014721 -0.1599 0.436611 44 -0.071922 -0.7813 0.218103 45 0.101489 1.1025 0.136254 46 0.026982 0.2931 0.384982 47 -0.037626 -0.4087 0.341741 48 -0.073236 -0.7955 0.213947

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/1fbc01302189510.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/1fbc01302189510.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/260cm1302189510.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/260cm1302189510.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/3wvp71302189510.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/07/t1302189422ib1lw5c7drpde21/3wvp71302189510.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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