*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, 27 May 2011 08:36:10 +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/27/t1306485132tsto0eyl3yqautd.htm/, Retrieved Fri, 27 May 2011 10:32:16 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

505,7 55,7 735,7 575,9 545,8 905,8 765,8 945,7 15,7 645,7 155,9 416 825,8 725,9 925,9 556 116,1 876,3 336,2 186,1 286,1 26 915,8 405,7 965,7 395,6 425,8 545,6 65,6 445,6 895,5 175,4 715,4 865,5 57,4 145,4 315,3 635,4 5,2 515,2 515,1 955 955 634,9 205 275 425 84,9 534,7 4,8 704,7 684,7 884,6 994,6 294,7 524,7 914,5 564,4 984,5 934,4 514,6 474,5 784,4 504,5 824,4 414,6 964,7 64,6 244,7 344,7 34,7 685 425 484,8 785,1 704,9 245,4 285,6 218,8 706,1 856,2 456,6 606,8 527,3 657,8 948,2 486,6 238,9 289,4 969,5 589,5 189,7 639,8 9710,1 969,9 939,9 859,7 679,9 879,9 329,8 349,6 39,5 849,5 449,6 749,6 249,7 649,8 619,4 939 778,9

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 'George Udny Yule' @ 216.218.223.82 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.4775 -4.9852 1e-06 2 -0.030721 -0.3207 0.374512 3 0.002168 0.0226 0.490991 4 0.024452 0.2553 0.39949 5 0.017028 0.1778 0.429612 6 -0.051047 -0.5329 0.297579 7 0.0035 0.0365 0.48546 8 -0.017034 -0.1778 0.429588 9 0.050194 0.524 0.300656 10 -0.029928 -0.3125 0.377647 11 0.047972 0.5008 0.308745 12 -0.089072 -0.9299 0.177228 13 0.071125 0.7426 0.229671 14 -0.02468 -0.2577 0.398573 15 0.014323 0.1495 0.440702 16 -0.007943 -0.0829 0.467032 17 -0.035835 -0.3741 0.354518 18 0.032163 0.3358 0.368837 19 0.01724 0.18 0.428749 20 -0.010129 -0.1058 0.457986 21 -0.015982 -0.1669 0.433894 22 0.03204 0.3345 0.369319 23 -0.032473 -0.339 0.36762 24 0.021284 0.2222 0.412283 25 -0.008178 -0.0854 0.466058 26 -0.050306 -0.5252 0.300253 27 0.074184 0.7745 0.220156 28 -0.049668 -0.5185 0.302565 29 0.042601 0.4448 0.328684 30 -0.032299 -0.3372 0.368303 31 0.02771 0.2893 0.386451 32 -0.020525 -0.2143 0.415361 33 -0.018626 -0.1945 0.423088 34 0.031373 0.3275 0.371944 35 0.004895 0.0511 0.479666 36 -0.025798 -0.2693 0.394088 37 0.030479 0.3182 0.375467 38 -0.007152 -0.0747 0.470306 39 -0.036897 -0.3852 0.350414 40 0.030222 0.3155 0.376482 41 0.002723 0.0284 0.488685 42 -0.001662 -0.0174 0.493095 43 0.024922 0.2602 0.397603 44 -0.047962 -0.5007 0.308782 45 0.038137 0.3982 0.345644 46 -0.037681 -0.3934 0.347397 47 0.029095 0.3038 0.380946 48 -0.010634 -0.111 0.455901 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.4775 -4.9852 1e-06 2 -0.335142 -3.499 0.000339 3 -0.25894 -2.7034 0.003982 4 -0.176728 -1.8451 0.033869 5 -0.095485 -0.9969 0.160512 6 -0.12167 -1.2703 0.103347 7 -0.127686 -1.3331 0.092642 8 -0.163855 -1.7107 0.044991 9 -0.104089 -1.0867 0.139779 10 -0.109634 -1.1446 0.127438 11 -0.020947 -0.2187 0.413651 12 -0.117651 -1.2283 0.110987 13 -0.064227 -0.6705 0.251963 14 -0.080155 -0.8368 0.202256 15 -0.05225 -0.5455 0.293261 16 -0.043311 -0.4522 0.326019 17 -0.0924 -0.9647 0.168419 18 -0.092014 -0.9607 0.169425 19 -0.053401 -0.5575 0.289156 20 -0.047633 -0.4973 0.309989 21 -0.048787 -0.5093 0.305768 22 -0.010095 -0.1054 0.458128 23 -0.034458 -0.3598 0.359864 24 -0.026561 -0.2773 0.391036 25 -0.013995 -0.1461 0.442051 26 -0.101735 -1.0621 0.14526 27 -0.032843 -0.3429 0.36617 28 -0.077373 -0.8078 0.210485 29 -0.036184 -0.3778 0.353168 30 -0.054302 -0.5669 0.285966 31 -0.02139 -0.2233 0.411851 32 -0.042696 -0.4458 0.328329 33 -0.090061 -0.9403 0.174582 34 -0.070404 -0.735 0.231946 35 -0.040666 -0.4246 0.335995 36 -0.06396 -0.6678 0.252849 37 -0.015289 -0.1596 0.436736 38 -0.020703 -0.2161 0.414637 39 -0.061762 -0.6448 0.260201 40 -0.070777 -0.7389 0.230766 41 -0.04609 -0.4812 0.315671 42 -0.04541 -0.4741 0.31819 43 0.022791 0.2379 0.406185 44 -0.018295 -0.191 0.424437 45 0.019043 0.1988 0.421389 46 -0.027364 -0.2857 0.387828 47 0.000249 0.0026 0.498965 48 0.001841 0.0192 0.492349

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/156px1306485367.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/156px1306485367.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/2fren1306485367.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/2fren1306485367.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/3bac31306485367.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/27/t1306485132tsto0eyl3yqautd/3bac31306485367.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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