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autocorrelatie

*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: Wed, 15 Dec 2010 16:41:13 +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/15/t12924311510gdynr2tejy1rme.htm/, Retrieved Wed, 15 Dec 2010 17:39:11 +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/15/t12924311510gdynr2tejy1rme.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 «

1.3031 1.3241 1.2961 1.2865 1.2305 1.2101 1.2125 1.2350 1.2014 1.1992 1.1791 1.1832 1.2159 1.1922 1.2114 1.2614 1.2812 1.2786 1.2772 1.2815 1.2679 1.2765 1.3247 1.3191 1.3029 1.3234 1.3354 1.3651 1.3453 1.3534 1.3706 1.3638 1.4268 1.4485 1.4635 1.4587 1.4876 1.5189 1.5783 1.5633 1.5554 1.5757 1.5593 1.4660 1.4065 1.2759 1.2705 1.3954 1.2793 1.2694 1.3282 1.3230 1.4135 1.4042 1.4253 1.4322 1.4632 1.4713 1.5016 1.4318

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.194927	1.3364	0.093934
2	-0.068698	-0.471	0.319921
3	0.012984	0.089	0.464726
4	-0.051592	-0.3537	0.362573
5	0.17837	1.2228	0.113742
6	0.04065	0.2787	0.390855
7	-0.255549	-1.752	0.043152
8	-0.153646	-1.0533	0.148784
9	-0.097456	-0.6681	0.25366
10	-0.003858	-0.0264	0.489506
11	0.044066	0.3021	0.381954
12	-0.431824	-2.9604	0.002401
13	-0.250996	-1.7207	0.045938
14	0.099557	0.6825	0.249127
15	0.160183	1.0982	0.138865
16	0.101825	0.6981	0.244283
17	0.073278	0.5024	0.308877
18	8e-04	0.0055	0.497823
19	-0.003757	-0.0258	0.489781
20	0.114781	0.7869	0.217646
21	0.010712	0.0734	0.470884
22	0.037912	0.2599	0.398034
23	-0.14887	-1.0206	0.156334
24	0.013801	0.0946	0.46251
25	0.121856	0.8354	0.203858
26	-0.026911	-0.1845	0.42721
27	-0.111496	-0.7644	0.224231
28	-0.151354	-1.0376	0.152375
29	-0.133726	-0.9168	0.18197
30	-0.02834	-0.1943	0.423393
31	0.038695	0.2653	0.395978
32	0.045333	0.3108	0.378667
33	-0.026007	-0.1783	0.42963
34	-0.090871	-0.623	0.268154
35	0.127279	0.8726	0.193664
36	0.064267	0.4406	0.330764
37	-0.040311	-0.2764	0.391743
38	0.007834	0.0537	0.478698
39	-0.00233	-0.016	0.493662
40	0.097626	0.6693	0.253294
41	0.090205	0.6184	0.269645
42	0.030066	0.2061	0.418792
43	-0.049435	-0.3389	0.368094
44	-0.075243	-0.5158	0.304192
45	-0.048095	-0.3297	0.371537
46	0.043357	0.2972	0.383796
47	NA	NA	NA
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.194927	1.3364	0.093934
2	-0.110908	-0.7604	0.225421
3	0.052074	0.357	0.361345
4	-0.077062	-0.5283	0.299885
5	0.224564	1.5395	0.06519
6	-0.071821	-0.4924	0.312372
7	-0.225135	-1.5434	0.064714
8	-0.078375	-0.5373	0.296793
9	-0.069443	-0.4761	0.318113
10	0.00205	0.0141	0.494423
11	-0.001835	-0.0126	0.495007
12	-0.432164	-2.9628	0.002386
13	-0.055671	-0.3817	0.352217
14	0.090223	0.6185	0.269604
15	0.146944	1.0074	0.159451
16	-0.088763	-0.6085	0.272884
17	0.193678	1.3278	0.09533
18	0.050177	0.344	0.366191
19	-0.217174	-1.4889	0.071601
20	-0.058696	-0.4024	0.344608
21	-0.080594	-0.5525	0.291603
22	0.117982	0.8088	0.211341
23	-0.202139	-1.3858	0.086175
24	0.03204	0.2197	0.413545
25	-0.019259	-0.132	0.44776
26	0.054431	0.3732	0.355352
27	-0.026206	-0.1797	0.429096
28	-0.169726	-1.1636	0.125233
29	0.018491	0.1268	0.449833
30	-0.008719	-0.0598	0.476293
31	-0.106293	-0.7287	0.234897
32	-0.004448	-0.0305	0.487901
33	-0.087049	-0.5968	0.27676
34	0.047944	0.3287	0.371926
35	-0.054065	-0.3707	0.356281
36	-0.02426	-0.1663	0.434309
37	-0.067267	-0.4612	0.323406
38	0.067902	0.4655	0.321857
39	-0.031177	-0.2137	0.415839
40	-0.081433	-0.5583	0.289653
41	0.003534	0.0242	0.490386
42	-0.012395	-0.085	0.46632
43	-0.037675	-0.2583	0.398657
44	-0.052459	-0.3596	0.360364
45	-0.016683	-0.1144	0.454714
46	-0.032967	-0.226	0.411088
47	NA	NA	NA
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/17kky1292431269.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/17kky1292431269.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/2ht1j1292431269.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/2ht1j1292431269.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/3ak0m1292431269.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t12924311510gdynr2tejy1rme/3ak0m1292431269.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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')

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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