datareeks - degree of non-seasonal differencing gemiddelde gokuitgaven per dag - frederik Verbraken

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Fri, 20 May 2011 11:26:35 +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/May/20/t1305890673idvdfm0rbnvlkai.htm/, Retrieved Fri, 20 May 2011 13:24:36 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

5.81 5.76 5.99 6.12 6.03 6.25 5.80 5.67 5.89 5.91 5.86 6.07 6.27 6.68 6.77 6.71 6.62 6.50 5.89 6.05 6.43 6.47 6.62 6.77 6.70 6.95 6.73 7.07 7.28 7.32 6.76 6.93 6.99 7.16 7.28 7.08 7.34 7.87 6.28 6.30 6.36 6.28 5.89 6.04 5.96 6.10 6.26 6.02 6.25 6.41 6.22 6.57 6.18 6.26 6.10 6.02 6.06 6.35 6.21 6.48 6.74 6.53 6.80 6.75 6.56 6.66 6.18 6.40 6.43 6.54 6.44 6.64 6.82 6.97 7.00 6.91 6.74 6.98 6.37 6.56 6.63 6.87 6.68 6.75 6.84 7.15 7.09 6.97 7.15

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 3 seconds R Server 'Gwilym Jenkins' @ www.wessa.org Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.243535 -2.2846 0.012372 2 -0.063517 -0.5958 0.276404 3 0.067123 0.6297 0.265271 4 -0.003586 -0.0336 0.486622 5 -0.127153 -1.1928 0.118077 6 -0.011052 -0.1037 0.45883 7 -0.25608 -2.4022 0.009198 8 0.204275 1.9163 0.029288 9 0.087266 0.8186 0.207606 10 -0.165224 -1.5499 0.062372 11 -0.052533 -0.4928 0.31169 12 0.377804 3.5441 0.000317 13 -0.253432 -2.3774 0.009801 14 0.245638 2.3043 0.011781 15 -0.159691 -1.498 0.068851 16 -0.022101 -0.2073 0.418119 17 0.072342 0.6786 0.249577 18 -0.159665 -1.4978 0.068884 19 -0.215159 -2.0184 0.023299 20 0.2501 2.3461 0.010608 21 -0.102259 -0.9593 0.170025 22 -0.045154 -0.4236 0.336453 23 0.154404 1.4484 0.075525 24 0.082335 0.7724 0.220982 25 -0.116784 -1.0955 0.138137 26 0.169772 1.5926 0.057417 27 -0.264685 -2.483 0.007463 28 0.190578 1.7878 0.038627 29 -0.060504 -0.5676 0.285883 30 -0.176249 -1.6534 0.05091 31 0.019195 0.1801 0.428756 32 0.155764 1.4612 0.073762 33 -0.178762 -1.6769 0.048552 34 0.067932 0.6373 0.262806 35 -0.00389 -0.0365 0.485488 36 0.037231 0.3493 0.363867 37 0.069774 0.6545 0.257237 38 0.038351 0.3598 0.359943 39 -0.168189 -1.5778 0.059105 40 0.255211 2.3941 0.009392 41 -0.148331 -1.3915 0.083796 42 -0.087049 -0.8166 0.208183 43 -0.028978 -0.2718 0.393192 44 0.03323 0.3117 0.377993 45 -0.030751 -0.2885 0.386834 46 0.054912 0.5151 0.30388 47 -0.1012 -0.9493 0.172523 48 0.16646 1.5615 0.060993 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.243535 -2.2846 0.012372 2 -0.13057 -1.2249 0.111949 3 0.01929 0.181 0.42841 4 0.012407 0.1164 0.453804 5 -0.124833 -1.171 0.122372 6 -0.086035 -0.8071 0.210898 7 -0.335526 -3.1475 0.001124 8 0.05209 0.4886 0.313153 9 0.131728 1.2357 0.109927 10 -0.093107 -0.8734 0.192405 11 -0.182791 -1.7147 0.044957 12 0.266306 2.4982 0.007171 13 -0.118854 -1.115 0.133954 14 0.269371 2.5269 0.006647 15 -0.08752 -0.821 0.20693 16 -0.04083 -0.383 0.351314 17 -0.006188 -0.058 0.476921 18 -0.165594 -1.5534 0.061957 19 -0.084218 -0.79 0.215814 20 0.029974 0.2812 0.389615 21 -0.072801 -0.6829 0.248221 22 -0.091016 -0.8538 0.197767 23 0.106622 1.0002 0.159977 24 0.041662 0.3908 0.348438 25 -0.032027 -0.3004 0.382273 26 -0.063478 -0.5955 0.276526 27 -0.06516 -0.6113 0.271304 28 0.09019 0.8461 0.199908 29 -0.079861 -0.7492 0.227878 30 -0.028838 -0.2705 0.393696 31 -0.03655 -0.3429 0.366256 32 0.017307 0.1624 0.4357 33 -0.036595 -0.3433 0.3661 34 -0.052155 -0.4893 0.31294 35 -0.06551 -0.6145 0.270224 36 -0.040071 -0.3759 0.353947 37 -0.030971 -0.2905 0.386047 38 0.077908 0.7308 0.233408 39 0.042415 0.3979 0.345838 40 -0.014644 -0.1374 0.445526 41 0.035073 0.329 0.371462 42 -0.05001 -0.4691 0.320068 43 -0.083822 -0.7863 0.216896 44 -0.013649 -0.128 0.449204 45 -0.006707 -0.0629 0.474987 46 -0.068637 -0.6439 0.260667 47 -0.03222 -0.3022 0.381588 48 0.044526 0.4177 0.338594

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/1g2ev1305890792.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/1g2ev1305890792.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/2nkdd1305890792.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/2nkdd1305890792.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/3e0dy1305890792.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305890673idvdfm0rbnvlkai/3e0dy1305890792.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 = 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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