seasonal diff geboortes

*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, 03 Dec 2010 12:15:13 +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/03/t1291378438tgij234uvnvqou2.htm/, Retrieved Fri, 03 Dec 2010 13:14:00 +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/03/t1291378438tgij234uvnvqou2.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:

» Textbox « » Textfile « » CSV «

9769 9321 9939 9336 10195 9464 10010 10213 9563 9890 9305 9391 9928 8686 9843 9627 10074 9503 10119 10000 9313 9866 9172 9241 9659 8904 9755 9080 9435 8971 10063 9793 9454 9759 8820 9403 9676 8642 9402 9610 9294 9448 10319 9548 9801 9596 8923 9746 9829 9125 9782 9441 9162 9915 10444 10209 9985 9842 9429 10132 9849 9172 10313 9819 9955 10048 10082 10541 10208 10233 9439 9963 10158 9225 10474 9757 10490 10281 10444 10640 10695 10786 9832 9747 10411 9511 10402 9701 10540 10112 10915 11183 10384 10834 9886 10216

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' @ 72.249.127.135 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.42054 -3.8313 0.000123 2 -0.131828 -1.201 0.116581 3 0.083562 0.7613 0.224321 4 -0.121906 -1.1106 0.13497 5 0.12458 1.135 0.129825 6 0.055874 0.509 0.306039 7 -0.102733 -0.9359 0.176008 8 -0.089989 -0.8198 0.207327 9 0.256402 2.3359 0.010953 10 -0.120827 -1.1008 0.137086 11 0.031931 0.2909 0.385923 12 -0.081615 -0.7436 0.229624 13 -0.184585 -1.6817 0.048198 14 0.322963 2.9423 0.002111 15 -0.072519 -0.6607 0.255324 16 -0.083127 -0.7573 0.225501 17 0.038193 0.348 0.364377 18 0.097328 0.8867 0.188901 19 -0.109359 -0.9963 0.160999 20 -0.017903 -0.1631 0.435418 21 0.06416 0.5845 0.280226 22 -0.178526 -1.6265 0.053822 23 0.301069 2.7429 0.00373 24 -0.115081 -1.0484 0.148741 25 -0.074561 -0.6793 0.249425 26 0.004913 0.0448 0.482202 27 0.058866 0.5363 0.296595 28 -0.018547 -0.169 0.433114 29 0.025131 0.229 0.409733 30 -0.066279 -0.6038 0.273802 31 -0.124907 -1.138 0.129207 32 0.243682 2.22 0.014571 33 -0.032973 -0.3004 0.382312 34 -0.095785 -0.8726 0.192687 35 0.077051 0.702 0.242331 36 -0.150249 -1.3688 0.087373 37 0.086847 0.7912 0.215537 38 0.087484 0.797 0.213857 39 -0.078774 -0.7177 0.237488 40 -0.044605 -0.4064 0.342757 41 0.103979 0.9473 0.173119 42 -0.08091 -0.7371 0.231562 43 0.060748 0.5534 0.290726 44 0.014419 0.1314 0.447903 45 -0.130397 -1.188 0.119116 46 0.100568 0.9162 0.181103 47 0.041309 0.3763 0.353811 48 -0.123997 -1.1297 0.130935 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.42054 -3.8313 0.000123 2 -0.375003 -3.4164 0.000492 3 -0.21257 -1.9366 0.028098 4 -0.328622 -2.9939 0.001814 5 -0.171937 -1.5664 0.060527 6 -0.039064 -0.3559 0.361412 7 -0.06212 -0.5659 0.286481 8 -0.231745 -2.1113 0.018877 9 0.116125 1.058 0.146573 10 0.073674 0.6712 0.251977 11 0.177367 1.6159 0.054956 12 0.021945 0.1999 0.421011 13 -0.263992 -2.4051 0.009196 14 -0.034242 -0.312 0.377926 15 -0.087412 -0.7964 0.214048 16 -0.135946 -1.2385 0.109506 17 -0.103613 -0.944 0.173965 18 0.180742 1.6466 0.051707 19 0.118843 1.0827 0.141035 20 -0.04948 -0.4508 0.32666 21 0.07449 0.6786 0.249629 22 -0.066781 -0.6084 0.27229 23 0.114779 1.0457 0.149372 24 0.000456 0.0042 0.498349 25 -0.059534 -0.5424 0.294504 26 -0.149668 -1.3635 0.0882 27 0.038217 0.3482 0.364295 28 -0.050004 -0.4556 0.32495 29 0.05182 0.4721 0.319045 30 0.040482 0.3688 0.356605 31 -0.116094 -1.0577 0.146638 32 -0.178334 -1.6247 0.054009 33 -0.057252 -0.5216 0.301673 34 -0.074052 -0.6746 0.250889 35 0.041623 0.3792 0.352752 36 -0.042115 -0.3837 0.351097 37 -0.114645 -1.0445 0.149651 38 -0.063457 -0.5781 0.282373 39 -0.009192 -0.0837 0.46673 40 0.007086 0.0646 0.474341 41 -0.009514 -0.0867 0.46557 42 -0.071954 -0.6555 0.25697 43 -0.019468 -0.1774 0.429828 44 -0.081084 -0.7387 0.231082 45 0.019114 0.1741 0.43109 46 0.006528 0.0595 0.476358 47 0.129655 1.1812 0.120445 48 -0.06586 -0.6 0.275066

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/03/t1291378438tgij234uvnvqou2/1sfsc1291378511.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/03/t1291378438tgij234uvnvqou2/1sfsc1291378511.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/03/t1291378438tgij234uvnvqou2/23orx1291378511.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/03/t1291378438tgij234uvnvqou2/23orx1291378511.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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 (par2 == 0) { x <- log(x) } else { x <- (x ^ par2 - 1) / par2 } if (par3 > 0) x <- diff(x,lag=1,difference=par3) if (par4 > 0) x <- diff(x,lag=par5,difference=par4) bitmap(file='pic1.png') racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')) dev.off() bitmap(file='pic2.png') rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') 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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