Opdracht 6 bis IKO - Autocorrelatie trend Bouwvergunningen - Nathan Jacobs

*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, 26 Apr 2011 14:59:58 +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/26/t1303829818cdcef50k0kfmam1.htm/, Retrieved Tue, 26 Apr 2011 16:57:21 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

1394 1657 2411 3595 3336 3249 2920 2113 2040 1853 1832 2093 2164 2368 2072 2521 1819 1947 2226 1754 1787 2072 1846 2137 2467 2154 2289 2628 2074 2798 2194 2442 2565 2063 2069 2539 1898 2139 2408 2725 2201 2311 2548 2276 2351 2280 2057 2479 2379 2295 2456 2546 2844 2260 2981 2678 3440 2842 2450 2669 2570 2540 2318 2930 2947 2799 2695 2498 2260 2160 2058 2533 2150 2172 2155 3016 2333 2355 2825 2214 2360 2299 1746 2069 2267 1878 2266 2282 2085 2277 2251 1828 1954 1851 1570 1852 2187 1855 2218

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 -0.330042 -3.2673 0.000749 2 0.011221 0.1111 0.45589 3 0.162987 1.6135 0.054927 4 -0.205331 -2.0327 0.022395 5 -0.12677 -1.255 0.106239 6 0.029606 0.2931 0.38504 7 -0.123855 -1.2261 0.111548 8 0.005039 0.0499 0.480157 9 0.172852 1.7112 0.045108 10 -0.062599 -0.6197 0.268448 11 -0.071502 -0.7078 0.240365 12 0.255308 2.5274 0.006545 13 -0.182104 -1.8027 0.037251 14 -0.022567 -0.2234 0.411843 15 0.140496 1.3908 0.083712 16 -0.174828 -1.7307 0.043325 17 0.029146 0.2885 0.386774 18 -0.016761 -0.1659 0.434278 19 -0.014864 -0.1471 0.441659 20 -0.089228 -0.8833 0.189614 21 0.214505 2.1235 0.018116 22 -0.137524 -1.3614 0.088252 23 -0.014533 -0.1439 0.44295 24 0.15261 1.5108 0.067033 25 -0.026279 -0.2601 0.397647 26 -0.027747 -0.2747 0.39207 27 0.091392 0.9047 0.183913 28 -0.076841 -0.7607 0.224335 29 0.025757 0.255 0.399636 30 -0.009497 -0.094 0.462643 31 -0.135361 -1.34 0.091672 32 0.071312 0.706 0.240946 33 0.017051 0.1688 0.43315 34 0.002928 0.029 0.488467 35 -0.116727 -1.1555 0.125341 36 0.212104 2.0997 0.019161 37 -0.040088 -0.3969 0.346169 38 -0.133832 -1.3249 0.094147 39 0.135961 1.3459 0.090713 40 -0.051565 -0.5105 0.305435 41 -0.03627 -0.3591 0.360162 42 0.036577 0.3621 0.359032 43 -0.057571 -0.5699 0.285016 44 0.019643 0.1945 0.423109 45 -0.054192 -0.5365 0.296422 46 0.119317 1.1812 0.120194 47 -0.173856 -1.7211 0.044195 48 0.103279 1.0224 0.154553 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.330042 -3.2673 0.000749 2 -0.109651 -1.0855 0.140183 3 0.148697 1.472 0.072109 4 -0.114534 -1.1338 0.129816 5 -0.263792 -2.6114 0.005217 6 -0.155632 -1.5407 0.063309 7 -0.14531 -1.4385 0.07674 8 -0.087491 -0.8661 0.194271 9 0.099449 0.9845 0.163649 10 0.002727 0.027 0.489259 11 -0.201457 -1.9943 0.024448 12 0.090484 0.8957 0.186293 13 -0.016435 -0.1627 0.435547 14 -0.048425 -0.4794 0.316369 15 0.054981 0.5443 0.29374 16 -0.052944 -0.5241 0.30069 17 -0.0358 -0.3544 0.361899 18 -0.129861 -1.2856 0.100813 19 0.010217 0.1011 0.459823 20 -0.132146 -1.3082 0.096937 21 0.092781 0.9185 0.18031 22 -0.051677 -0.5116 0.305048 23 -0.108354 -1.0726 0.143032 24 -0.042236 -0.4181 0.338387 25 0.130004 1.287 0.100567 26 0.072798 0.7207 0.236417 27 0.009189 0.091 0.463853 28 0.016183 0.1602 0.436526 29 0.041981 0.4156 0.33931 30 0.018365 0.1818 0.428055 31 -0.106243 -1.0517 0.147751 32 0.084123 0.8328 0.203498 33 -0.02022 -0.2002 0.420882 34 0.067685 0.67 0.252203 35 -0.18448 -1.8263 0.035428 36 0.042014 0.4159 0.33919 37 0.106605 1.0553 0.146933 38 -0.122558 -1.2133 0.113973 39 0.010623 0.1052 0.458229 40 0.002319 0.023 0.490864 41 0.055184 0.5463 0.293053 42 -0.084929 -0.8408 0.201265 43 0.044852 0.444 0.329006 44 0.007661 0.0758 0.469851 45 -0.144817 -1.4336 0.077432 46 0.086012 0.8515 0.19829 47 -0.084515 -0.8367 0.202411 48 -0.086206 -0.8534 0.197761

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/1n49o1303829995.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/1n49o1303829995.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/28tu51303829995.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/28tu51303829995.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/390t71303829995.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/26/t1303829818cdcef50k0kfmam1/390t71303829995.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; 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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