| BEL20-ACF | *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, 20 Dec 2010 11:53:46 +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/20/t1292845912rn8sfp9qsb1c3i8.htm/, Retrieved Mon, 20 Dec 2010 12:51:56 +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/20/t1292845912rn8sfp9qsb1c3i8.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 « | 3030
2803
2768
2883
2863
2897
3013
3143
3033
3046
3111
3013
2987
2996
2833
2849
2795
2845
2915
2893
2604
2642
2660
2639
2720
2746
2736
2812
2799
2555
2305
2215
2066
1940
2042
1995
1947
1766
1635
1833
1910
1960
1970
2061
2093
2121
2175
2197
2350
2440
2409
2473
2408
2455
2448
2498
2646
2757
2849
2921
2982
3081
3106
3119
3061
3097
3162
3257
3277
3295
3364
3494
3667
3813
3918
3896
3801
3570
3702
3862
3970
4139
4200
4291
4444
4503
4357
4591
4697
4621
4563
4203
4296
4435
4105
4117
3844
3721
3674
3858
3801
3504
3033
3047
2962
2198
2014
1863
1905
1811
1670
1864
2052
2030
2071
2293
2443
2513
2467
2503
2540
2483
2626
2656
2447
2467
2462
2505
2579
2649
2637 | | Output produced by software: |
Autocorrelation Function | Time lag k | ACF(k) | T-STAT | P-value | 1 | 0.272701 | 3.1093 | 0.001152 | 2 | 0.059557 | 0.679 | 0.249157 | 3 | 0.214089 | 2.441 | 0.007997 | 4 | 0.17184 | 1.9593 | 0.02611 | 5 | 0.18402 | 2.0982 | 0.018914 | 6 | 0.016199 | 0.1847 | 0.426878 | 7 | 0.000389 | 0.0044 | 0.498234 | 8 | 0.123823 | 1.4118 | 0.080199 | 9 | 0.042348 | 0.4828 | 0.315011 | 10 | -0.099417 | -1.1335 | 0.129539 | 11 | 0.088115 | 1.0047 | 0.158462 | 12 | 0.023795 | 0.2713 | 0.393294 | 13 | -0.040977 | -0.4672 | 0.320566 | 14 | 0.052143 | 0.5945 | 0.276599 | 15 | 0.00142 | 0.0162 | 0.493552 | 16 | 0.06245 | 0.712 | 0.238859 | 17 | -0.080824 | -0.9215 | 0.17924 | 18 | -0.105552 | -1.2035 | 0.115489 | 19 | 0.059963 | 0.6837 | 0.247696 | 20 | -0.128769 | -1.4682 | 0.072234 | 21 | -0.12514 | -1.4268 | 0.078015 | 22 | -0.08598 | -0.9803 | 0.164373 | 23 | -0.128159 | -1.4612 | 0.073181 | 24 | -0.088012 | -1.0035 | 0.158745 | 25 | -0.075433 | -0.8601 | 0.195667 | 26 | -0.147382 | -1.6804 | 0.04764 | 27 | -0.036825 | -0.4199 | 0.337636 | 28 | 0.01517 | 0.173 | 0.431476 | 29 | -0.036253 | -0.4133 | 0.340018 | 30 | 0.017652 | 0.2013 | 0.420403 | 31 | -0.081718 | -0.9317 | 0.176602 | 32 | -0.008937 | -0.1019 | 0.459496 | 33 | -0.017948 | -0.2046 | 0.419089 | 34 | -0.073673 | -0.84 | 0.201226 | 35 | -0.097476 | -1.1114 | 0.134224 | 36 | -0.040263 | -0.4591 | 0.323475 | 37 | -0.071726 | -0.8178 | 0.207484 | 38 | -0.070243 | -0.8009 | 0.212328 | 39 | -0.011711 | -0.1335 | 0.446992 | 40 | -0.050074 | -0.5709 | 0.284515 | 41 | -0.01935 | -0.2206 | 0.412865 | 42 | -0.037649 | -0.4293 | 0.334219 | 43 | -0.091065 | -1.0383 | 0.15053 | 44 | 0.000402 | 0.0046 | 0.498176 | 45 | -0.063197 | -0.7206 | 0.236238 | 46 | -0.08089 | -0.9223 | 0.179044 | 47 | -0.061343 | -0.6994 | 0.242772 | 48 | -0.048087 | -0.5483 | 0.292219 | 49 | -0.077377 | -0.8822 | 0.18964 | 50 | -0.074867 | -0.8536 | 0.197445 | 51 | -0.08489 | -0.9679 | 0.167446 | 52 | -0.116289 | -1.3259 | 0.093598 | 53 | -0.019449 | -0.2218 | 0.412426 | 54 | -0.026513 | -0.3023 | 0.381456 | 55 | -0.03242 | -0.3696 | 0.356126 | 56 | 0.003092 | 0.0353 | 0.485966 | 57 | -0.04126 | -0.4704 | 0.319414 | 58 | -0.041828 | -0.4769 | 0.317112 | 59 | -0.013552 | -0.1545 | 0.43872 | 60 | 0.019919 | 0.2271 | 0.410346 |
Partial Autocorrelation Function | Time lag k | PACF(k) | T-STAT | P-value | 1 | 0.272701 | 3.1093 | 0.001152 | 2 | -0.015999 | -0.1824 | 0.427769 | 3 | 0.218231 | 2.4882 | 0.007051 | 4 | 0.064469 | 0.7351 | 0.231813 | 5 | 0.141331 | 1.6114 | 0.054756 | 6 | -0.115286 | -1.3145 | 0.095502 | 7 | -0.010086 | -0.115 | 0.454312 | 8 | 0.061385 | 0.6999 | 0.242621 | 9 | -0.020302 | -0.2315 | 0.408655 | 10 | -0.122997 | -1.4024 | 0.081593 | 11 | 0.153755 | 1.7531 | 0.040973 | 12 | -0.072489 | -0.8265 | 0.205016 | 13 | -0.010171 | -0.116 | 0.453928 | 14 | 0.060054 | 0.6847 | 0.247369 | 15 | 0.001034 | 0.0118 | 0.495308 | 16 | 0.032154 | 0.3666 | 0.357252 | 17 | -0.13957 | -1.5913 | 0.056981 | 18 | -0.017439 | -0.1988 | 0.421352 | 19 | 0.041655 | 0.4749 | 0.317812 | 20 | -0.187261 | -2.1351 | 0.017314 | 21 | 0.034487 | 0.3932 | 0.347403 | 22 | -0.076345 | -0.8705 | 0.192825 | 23 | -0.062405 | -0.7115 | 0.239016 | 24 | -0.012256 | -0.1397 | 0.444539 | 25 | 0.025776 | 0.2939 | 0.384653 | 26 | -0.074516 | -0.8496 | 0.198551 | 27 | 0.025637 | 0.2923 | 0.385258 | 28 | 0.072337 | 0.8248 | 0.205505 | 29 | 0.047873 | 0.5458 | 0.293059 | 30 | -0.043846 | -0.4999 | 0.30899 | 31 | -0.036762 | -0.4192 | 0.337897 | 32 | 0.04046 | 0.4613 | 0.32267 | 33 | -0.107353 | -1.224 | 0.11158 | 34 | 0.012646 | 0.1442 | 0.442786 | 35 | -0.108557 | -1.2377 | 0.109022 | 36 | 0.05587 | 0.637 | 0.262617 | 37 | -0.091439 | -1.0426 | 0.149543 | 38 | 0.012783 | 0.1457 | 0.442173 | 39 | 0.063543 | 0.7245 | 0.235031 | 40 | -0.058068 | -0.6621 | 0.254547 | 41 | -0.014105 | -0.1608 | 0.436244 | 42 | 0.01731 | 0.1974 | 0.421926 | 43 | -0.157479 | -1.7955 | 0.037446 | 44 | 0.027342 | 0.3117 | 0.377867 | 45 | -0.080503 | -0.9179 | 0.180192 | 46 | -0.025626 | -0.2922 | 0.385305 | 47 | -0.071115 | -0.8108 | 0.209471 | 48 | 0.005191 | 0.0592 | 0.476448 | 49 | -0.03754 | -0.428 | 0.334673 | 50 | -0.011021 | -0.1257 | 0.450097 | 51 | -0.070211 | -0.8005 | 0.212433 | 52 | -0.033891 | -0.3864 | 0.349912 | 53 | -0.010794 | -0.1231 | 0.451121 | 54 | 0.060741 | 0.6925 | 0.244914 | 55 | -0.078834 | -0.8988 | 0.185199 | 56 | 0.07027 | 0.8012 | 0.212239 | 57 | -0.103767 | -1.1831 | 0.119458 | 58 | -0.072805 | -0.8301 | 0.204 | 59 | 0.015239 | 0.1738 | 0.431164 | 60 | 0.003835 | 0.0437 | 0.482597 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/1xahx1292846024.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/1xahx1292846024.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/28jhi1292846024.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/28jhi1292846024.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/38jhi1292846024.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292845912rn8sfp9qsb1c3i8/38jhi1292846024.ps (open in new window) |
| | Parameters (Session): | par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; | | Parameters (R input): | par1 = 60 ; 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')
| |
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