Gemiddelde Zomertemperatuur Nederland

*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 15:40:53 +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/t13025362891y65d93efpr0fa2.htm/, Retrieved Mon, 11 Apr 2011 17:38:12 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

17 16,7 15,4 15,1 16,1 17 16,1 14,3 16,1 14,8 15,9 17,6 15,9 14,8 16,5 15,6 14,6 17,1 15,2 14,8 15,4 16,6 15,1 15,4 15,2 16,6 16,1 15,7 15,8 15,7 16,9 15,9 17,1 17 16,6 17,1 16,6 16,6 16,5 17 15,9 17 16,1 16,1 16,8 16,7 15,7 18,7 16,1 16,3 17,2 16,1 16,5 16,5 15,1 16,7 14,4 16,2 15,9 17,3 15,6 15,6 14,7 15,8 15,8 14,8 16,1 16,3 16,1 17,4 16,7 16,1 15,4 16,9 15,5 17,6 18,4 15,9 15,2 15,5 15,9 15,8 17,6 18,2 15,9 15,7 16,4 15,6 15,8 17 16,8 16,6 17,7 15,7 18 18,2 16,4 18 16,3

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 0.122497 1.2188 0.112902 2 0.079609 0.7921 0.215097 3 0.192558 1.9159 0.02913 4 -0.008418 -0.0838 0.466709 5 0.034204 0.3403 0.367166 6 0.292244 2.9078 0.002247 7 0.126084 1.2545 0.106303 8 0.034611 0.3444 0.365647 9 0.053594 0.5332 0.297528 10 -0.00924 -0.0919 0.463466 11 -0.026891 -0.2676 0.394797 12 0.061131 0.6082 0.272208 13 -0.013836 -0.1377 0.445393 14 0.045513 0.4529 0.325823 15 -0.056862 -0.5658 0.286414 16 0.045063 0.4484 0.327431 17 -0.065134 -0.6481 0.259219 18 -0.111242 -1.1068 0.135522 19 -0.052822 -0.5256 0.300182 20 -0.05094 -0.5068 0.306696 21 -0.057245 -0.5696 0.285127 22 0.023811 0.2369 0.406605 23 -0.093588 -0.9312 0.177012 24 -0.025523 -0.2539 0.400031 25 -0.04563 -0.454 0.325406 26 -0.065944 -0.6561 0.256629 27 -0.132849 -1.3218 0.094635 28 -0.07874 -0.7835 0.217615 29 -0.123943 -1.2332 0.110207 30 -0.091255 -0.908 0.183048 31 -0.118068 -1.1748 0.121453 32 -0.122233 -1.2162 0.113401 33 -0.019623 -0.1952 0.422799 34 -0.063334 -0.6302 0.265018 35 -0.033812 -0.3364 0.36863 36 0.102358 1.0185 0.155473 37 -0.023853 -0.2373 0.406445 38 0.01268 0.1262 0.449928 39 0.030654 0.305 0.380503 40 -0.057297 -0.5701 0.284952 41 -0.011278 -0.1122 0.455439 42 0.130189 1.2954 0.099103 43 0.020989 0.2088 0.417503 44 0.068116 0.6777 0.249758 45 0.077042 0.7666 0.222586 46 -0.005325 -0.053 0.478927 47 0.154525 1.5375 0.06368 48 0.079816 0.7942 0.214502 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.122497 1.2188 0.112902 2 0.065588 0.6526 0.257765 3 0.178853 1.7796 0.039108 4 -0.056563 -0.5628 0.287422 5 0.019235 0.1914 0.424307 6 0.270251 2.689 0.004206 7 0.085304 0.8488 0.19903 8 -0.031602 -0.3144 0.376924 9 -0.05744 -0.5715 0.284472 10 -0.019264 -0.1917 0.424194 11 -0.01967 -0.1957 0.422617 12 -0.008926 -0.0888 0.464704 13 -0.076578 -0.7619 0.223952 14 0.050418 0.5017 0.308513 15 -0.078428 -0.7803 0.218525 16 0.091198 0.9074 0.183196 17 -0.079229 -0.7883 0.216198 18 -0.102135 -1.0162 0.155999 19 -0.04033 -0.4013 0.344539 20 -0.017249 -0.1716 0.432043 21 0.011081 0.1103 0.456216 22 0.018061 0.1797 0.428876 23 -0.083014 -0.826 0.205402 24 0.071938 0.7158 0.237908 25 0.001816 0.0181 0.49281 26 -0.015552 -0.1547 0.438669 27 -0.132101 -1.3144 0.095876 28 -0.092417 -0.9195 0.180026 29 -0.041817 -0.4161 0.339129 30 -0.045016 -0.4479 0.327601 31 -0.096792 -0.9631 0.16893 32 -0.084313 -0.8389 0.201772 33 0.09648 0.96 0.169705 34 0.04569 0.4546 0.325194 35 0.055542 0.5526 0.290878 36 0.121106 1.205 0.115541 37 0.038835 0.3864 0.350012 38 0.046899 0.4666 0.320892 39 0.016475 0.1639 0.435062 40 -0.09438 -0.9391 0.174991 41 -0.037594 -0.3741 0.354582 42 0.065027 0.647 0.259561 43 0.018876 0.1878 0.425702 44 0.033323 0.3316 0.370462 45 -0.013564 -0.135 0.446459 46 -0.003722 -0.037 0.485266 47 0.192132 1.9117 0.029404 48 -0.016048 -0.1597 0.436731

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/1mcp41302536451.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/1mcp41302536451.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/2kuzj1302536451.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/2kuzj1302536451.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/3olex1302536451.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/11/t13025362891y65d93efpr0fa2/3olex1302536451.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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