| paper | *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: Mon, 27 Dec 2010 11:13:49 +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/27/t12934483347v6p75ufx7731e8.htm/, Retrieved Mon, 27 Dec 2010 12:12:15 +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/27/t12934483347v6p75ufx7731e8.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 « | 595.130
526.883
562.254
545.427
522.084
483.414
528.797
532.749
511.380
472.941
516.118
502.940
476.118
432.418
475.525
453.638
431.417
390.934
436.414
418.451
399.528
367.749
423.433
420.450
415.906
392.949
453.203
455.926
451.879
434.996
498.811
505.940
517.395
508.456
585.132
587.971
584.027
557.196
613.433
600.049
588.993
559.271
622.580
616.645
603.243
557.949
608.882
582.930
570.492
542.907
598.067
568.717
551.773
514.465
569.055
528.897
515.229
481.141
535.612
498.547
478.587
445.911
503.412
469.797
458.365
436.761
502.205
481.627
473.698
457.200
521.671
513.354
515.369
505.652
575.676
555.865
559.504
540.994
605.635
600.315
588.224
569.861
625.950
601.554
587.760
573.307
621.764
570.214
547.034
511.873
553.870
517.058
505.702
479.060
526.638
508.060
532.394
532.115
587.896
565.710
572.708
544.417
597.160 | | Output produced by software: |
Autocorrelation Function | Time lag k | ACF(k) | T-STAT | P-value | 1 | -0.214747 | -2.115 | 0.018496 | 2 | -0.000414 | -0.0041 | 0.498377 | 3 | 0.003383 | 0.0333 | 0.486746 | 4 | -0.341979 | -3.3681 | 0.000543 | 5 | 0.088268 | 0.8693 | 0.193405 | 6 | -0.01202 | -0.1184 | 0.453005 | 7 | 0.14365 | 1.4148 | 0.080167 | 8 | -0.080061 | -0.7885 | 0.21616 | 9 | -0.023513 | -0.2316 | 0.408679 | 10 | -0.035786 | -0.3525 | 0.362632 | 11 | -0.03373 | -0.3322 | 0.370227 | 12 | 0.135784 | 1.3373 | 0.092123 | 13 | -0.157992 | -1.556 | 0.061477 | 14 | 0.052846 | 0.5205 | 0.301959 | 15 | 0.011451 | 0.1128 | 0.455217 | 16 | -0.156136 | -1.5378 | 0.063682 | 17 | 0.15604 | 1.5368 | 0.063798 | 18 | 0.031846 | 0.3136 | 0.377232 | 19 | -0.067922 | -0.669 | 0.252558 | 20 | 0.082028 | 0.8079 | 0.210567 | 21 | -0.141823 | -1.3968 | 0.082831 | 22 | -0.016226 | -0.1598 | 0.436681 | 23 | 0.044057 | 0.4339 | 0.332657 | 24 | -0.012465 | -0.1228 | 0.451273 | 25 | 0.154016 | 1.5169 | 0.066275 | 26 | -0.115435 | -1.1369 | 0.12919 | 27 | 0.070107 | 0.6905 | 0.245772 | 28 | -0.051019 | -0.5025 | 0.308233 | 29 | -0.014231 | -0.1402 | 0.444411 | 30 | 0.121993 | 1.2015 | 0.116243 | 31 | -0.060396 | -0.5948 | 0.27667 | 32 | 0.021762 | 0.2143 | 0.41537 | 33 | 0.005404 | 0.0532 | 0.47883 | 34 | -0.104524 | -1.0294 | 0.152915 | 35 | 0.04572 | 0.4503 | 0.326754 | 36 | 0.037921 | 0.3735 | 0.354803 | 37 | 0.013002 | 0.1281 | 0.449187 | 38 | -0.098623 | -0.9713 | 0.166903 | 39 | 0.060119 | 0.5921 | 0.277579 | 40 | -0.009554 | -0.0941 | 0.462613 | 41 | -0.075947 | -0.748 | 0.228136 | 42 | 0.165357 | 1.6286 | 0.053323 | 43 | -0.080272 | -0.7906 | 0.215557 | 44 | -0.000654 | -0.0064 | 0.497438 | 45 | 0.00224 | 0.0221 | 0.49122 | 46 | -0.088393 | -0.8706 | 0.193068 | 47 | 0.132546 | 1.3054 | 0.097418 | 48 | -0.015615 | -0.1538 | 0.439049 | 49 | 0.035612 | 0.3507 | 0.363272 | 50 | -0.015282 | -0.1505 | 0.440337 | 51 | -0.069094 | -0.6805 | 0.248904 | 52 | -0.019032 | -0.1874 | 0.42585 | 53 | 0.002816 | 0.0277 | 0.488965 | 54 | 0.091793 | 0.9041 | 0.184102 | 55 | -0.023067 | -0.2272 | 0.41038 | 56 | -0.017294 | -0.1703 | 0.432554 | 57 | -0.026976 | -0.2657 | 0.395522 | 58 | -0.065061 | -0.6408 | 0.261591 | 59 | -0.041025 | -0.4041 | 0.343533 | 60 | -0.004464 | -0.044 | 0.482513 |
Partial Autocorrelation Function | Time lag k | PACF(k) | T-STAT | P-value | 1 | -0.214747 | -2.115 | 0.018496 | 2 | -0.04878 | -0.4804 | 0.316003 | 3 | -0.007551 | -0.0744 | 0.470433 | 4 | -0.360312 | -3.5487 | 0.000299 | 5 | -0.080904 | -0.7968 | 0.213752 | 6 | -0.039445 | -0.3885 | 0.349255 | 7 | 0.131205 | 1.2922 | 0.099676 | 8 | -0.1707 | -1.6812 | 0.047971 | 9 | -0.076263 | -0.7511 | 0.227203 | 10 | -0.074143 | -0.7302 | 0.233507 | 11 | 0.036471 | 0.3592 | 0.360114 | 12 | 0.051325 | 0.5055 | 0.307179 | 13 | -0.187894 | -1.8505 | 0.033639 | 14 | -0.086335 | -0.8503 | 0.198626 | 15 | 0.044803 | 0.4413 | 0.330004 | 16 | -0.116798 | -1.1503 | 0.126418 | 17 | -0.030212 | -0.2976 | 0.38334 | 18 | 0.038091 | 0.3752 | 0.354183 | 19 | -0.076582 | -0.7542 | 0.226265 | 20 | 0.022941 | 0.2259 | 0.410861 | 21 | -0.134183 | -1.3215 | 0.094714 | 22 | -0.070933 | -0.6986 | 0.243233 | 23 | -0.010966 | -0.108 | 0.457107 | 24 | -0.044179 | -0.4351 | 0.332223 | 25 | 0.08501 | 0.8372 | 0.202255 | 26 | -0.136558 | -1.3449 | 0.09089 | 27 | 0.038282 | 0.377 | 0.353488 | 28 | 0.021696 | 0.2137 | 0.415621 | 29 | -0.010472 | -0.1031 | 0.459033 | 30 | 0.065506 | 0.6452 | 0.260173 | 31 | 0.037133 | 0.3657 | 0.357686 | 32 | -0.077716 | -0.7654 | 0.22294 | 33 | 0.14362 | 1.4145 | 0.08021 | 34 | -0.103469 | -1.0191 | 0.155356 | 35 | -0.001485 | -0.0146 | 0.49418 | 36 | 0.077622 | 0.7645 | 0.223217 | 37 | 0.006867 | 0.0676 | 0.473108 | 38 | -0.11348 | -1.1176 | 0.133239 | 39 | 0.0441 | 0.4343 | 0.332505 | 40 | 0.05195 | 0.5117 | 0.305029 | 41 | -0.00988 | -0.0973 | 0.461341 | 42 | 0.006314 | 0.0622 | 0.47527 | 43 | 0.013463 | 0.1326 | 0.447394 | 44 | 0.031769 | 0.3129 | 0.377518 | 45 | -0.040525 | -0.3991 | 0.345339 | 46 | 0.035402 | 0.3487 | 0.364048 | 47 | 0.046223 | 0.4552 | 0.324975 | 48 | 0.034526 | 0.34 | 0.367281 | 49 | 0.107826 | 1.062 | 0.145444 | 50 | -0.068033 | -0.67 | 0.25221 | 51 | -0.007127 | -0.0702 | 0.472092 | 52 | 0.053272 | 0.5247 | 0.300505 | 53 | 0.014436 | 0.1422 | 0.443618 | 54 | 0.01419 | 0.1398 | 0.44457 | 55 | 0.038796 | 0.3821 | 0.351612 | 56 | -0.065602 | -0.6461 | 0.259867 | 57 | 0.005132 | 0.0505 | 0.479897 | 58 | -0.024545 | -0.2417 | 0.404744 | 59 | -0.128441 | -1.265 | 0.104451 | 60 | -0.144967 | -1.4278 | 0.078286 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/1nz1k1293448425.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/1nz1k1293448425.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/2g8i51293448425.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/2g8i51293448425.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/3rzhp1293448425.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/27/t12934483347v6p75ufx7731e8/3rzhp1293448425.ps (open in new window) |
| | Parameters (Session): | par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 4 ; par6 = White Noise ; par7 = 0.95 ; | | Parameters (R input): | par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 4 ; 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')
| |
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