Central tendency paper uitvoer Belgie

*The author of this computation has been verified*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Fri, 17 Dec 2010 14:53:08 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza.htm/, Retrieved Fri, 17 Dec 2010 15:58:43 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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14544 15116 17413 16181 15607 17160 14915 13768 17487 16198 17535 16571 16198 16554 19554 15903 18003 18329 16260 14851 18174 18406 18466 16016 17428 17167 19630 17183 18344 19301 18147 16192 18374 20515 18957 16471 18746 19009 19211 20547 19325 20605 20056 16141 20359 19711 15638 14384 13855 14308 15290 14423 13779 15686 14733 12522 16189 16059 16007 15806 15160

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.400291 -2.4017 0.010802 2 0.108348 0.6501 0.259881 3 0.389526 2.3372 0.012555 4 -0.333015 -1.9981 0.026652 5 0.241446 1.4487 0.078041 6 0.083087 0.4985 0.310575 7 -0.337525 -2.0251 0.025158 8 0.295421 1.7725 0.042385 9 -0.198052 -1.1883 0.121246 10 -0.081487 -0.4889 0.313932 11 0.10767 0.646 0.261181 12 -0.222671 -1.336 0.094962 13 -0.017091 -0.1025 0.459446 14 0.023834 0.143 0.443541 15 -0.051242 -0.3075 0.380136 16 -0.065965 -0.3958 0.347297 17 0.056565 0.3394 0.368144 18 -0.065403 -0.3924 0.348532 19 -0.016529 -0.0992 0.460774 20 0.076198 0.4572 0.325141 21 -0.036378 -0.2183 0.414226 22 -0.092136 -0.5528 0.291903 23 0.200648 1.2039 0.118245 24 -0.175204 -1.0512 0.150081 25 0.08209 0.4925 0.312664 26 0.000578 0.0035 0.498627 27 -0.103238 -0.6194 0.269767 28 0.131362 0.7882 0.217878 29 -0.070065 -0.4204 0.338349 30 -0.045697 -0.2742 0.392755 31 0.10515 0.6309 0.266045 32 -0.092474 -0.5548 0.291217 33 0.023136 0.1388 0.445185 34 -0.014335 -0.086 0.465969 35 -0.006261 -0.0376 0.485121 36 NA NA NA 37 NA NA NA 38 NA NA NA 39 NA NA NA 40 NA NA NA 41 NA NA NA 42 NA NA NA 43 NA NA NA 44 NA NA NA 45 NA NA NA 46 NA NA NA 47 NA NA NA 48 NA NA NA 49 NA NA NA 50 NA NA NA 51 NA NA NA 52 NA NA NA 53 NA NA NA 54 NA NA NA 55 NA NA NA 56 NA NA NA 57 NA NA NA 58 NA NA NA 59 NA NA NA 60 NA NA NA Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.400291 -2.4017 0.010802 2 -0.061784 -0.3707 0.356515 3 0.491111 2.9467 0.002802 4 0.002188 0.0131 0.4948 5 0.000174 0.001 0.499586 6 0.056144 0.3369 0.369089 7 -0.257578 -1.5455 0.06549 8 -0.070038 -0.4202 0.338409 9 -0.086221 -0.5173 0.304047 10 0.01143 0.0686 0.472852 11 -0.071134 -0.4268 0.336031 12 -0.060693 -0.3642 0.358936 13 -0.123587 -0.7415 0.231594 14 -0.078382 -0.4703 0.320492 15 0.200215 1.2013 0.118741 16 -0.05316 -0.319 0.3758 17 -0.00342 -0.0205 0.491872 18 -0.063597 -0.3816 0.352507 19 -0.0737 -0.4422 0.330495 20 -0.021244 -0.1275 0.449642 21 0.074726 0.4484 0.328292 22 -0.119552 -0.7173 0.238905 23 0.034648 0.2079 0.418244 24 -0.030341 -0.182 0.428285 25 -0.028039 -0.1682 0.433671 26 -0.13665 -0.8199 0.208834 27 0.007745 0.0465 0.481597 28 0.080343 0.4821 0.316341 29 -0.035176 -0.2111 0.417016 30 -0.004324 -0.0259 0.489722 31 -0.059878 -0.3593 0.360747 32 0.021632 0.1298 0.448727 33 -0.033549 -0.2013 0.4208 34 -0.129585 -0.7775 0.220969 35 0.030556 0.1833 0.427781 36 NA NA NA 37 NA NA NA 38 NA NA NA 39 NA NA NA 40 NA NA NA 41 NA NA NA 42 NA NA NA 43 NA NA NA 44 NA NA NA 45 NA NA NA 46 NA NA NA 47 NA NA NA 48 NA NA NA 49 NA NA NA 50 NA NA NA 51 NA NA NA 52 NA NA NA 53 NA NA NA 54 NA NA NA 55 NA NA NA 56 NA NA NA 57 NA NA NA 58 NA NA NA 59 NA NA NA 60 NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/1fsil1292597583.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/1fsil1292597583.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/2iah81292597583.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/2iah81292597583.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/3iah81292597583.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292597922dkcezclcowj5kza/3iah81292597583.ps (open in new window)

Parameters (Session):

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; 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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