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Autocorrelation Function - Verkoop wijn - Veronika Kaplova

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Sun, 09 May 2010 08:55:46 +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/May/09/t1273395418rczmsz621nl8krq.htm/, Retrieved Sun, 09 May 2010 10:57:00 +0200

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/May/09/t1273395418rczmsz621nl8krq.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:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

2550 2867 3458 2961 3163 2880 3331 3062 3534 3622 4464 5411 2564 2820 3508 3088 3299 2939 3320 3418 3604 3495 4163 4882 2211 3260 2992 2425 2707 3244 3965 3315 3333 3583 4021 4904 2252 2952 3573 3048 3059 2731 3563 3092 3478 3478 4308 5029 2075 3264 3308 3688 3136 2824 3644 4694 2914 3686 4358 5587 2265 3685 3754 3708 3210 3517 3905 3670 4221 4404 5086 5725 2367 3819 4067 4022 3937 4365 4290

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.125113	1.112	0.13475
2	-0.02936	-0.261	0.397403
3	0.080018	0.7112	0.239523
4	0.143277	1.2735	0.103293
5	-0.015521	-0.138	0.445313
6	-0.212344	-1.8874	0.031393
7	0.034945	0.3106	0.378463
8	0.125802	1.1182	0.133446
9	0.061416	0.5459	0.293344
10	-0.08162	-0.7255	0.235157
11	0.03975	0.3533	0.3624
12	0.650802	5.7845	0
13	0.015952	0.1418	0.443806
14	-0.067335	-0.5985	0.275614
15	0.038783	0.3447	0.365613
16	0.077581	0.6896	0.246249
17	-0.068664	-0.6103	0.271707
18	-0.247184	-2.197	0.015475
19	0.020561	0.1828	0.42773
20	0.036912	0.3281	0.371858
21	0.002786	0.0248	0.490155
22	-0.095633	-0.85	0.198945
23	0.017397	0.1546	0.438753
24	0.492402	4.3766	1.8e-05
25	-0.022466	-0.1997	0.421121
26	-0.079866	-0.7099	0.239939
27	-0.017595	-0.1564	0.438062
28	-0.012594	-0.1119	0.455579
29	-0.045461	-0.4041	0.343626
30	-0.21207	-1.8849	0.031559
31	-0.061491	-0.5465	0.293116
32	-0.022494	-0.1999	0.421022
33	-0.018699	-0.1662	0.434213
34	-0.140398	-1.2479	0.107879
35	-0.012199	-0.1084	0.456967
36	0.363263	3.2288	0.000906
37	-0.054744	-0.4866	0.313953
38	-0.08223	-0.7309	0.233509
39	-0.023328	-0.2073	0.418137
40	0.009299	0.0826	0.46717
41	-0.038498	-0.3422	0.366562
42	-0.183681	-1.6326	0.053267
43	-0.06199	-0.551	0.291603
44	-0.019978	-0.1776	0.429758
45	-0.014849	-0.132	0.447669
46	-0.108878	-0.9677	0.168066
47	-0.011625	-0.1033	0.458985
48	0.244462	2.1728	0.016395
49	-0.050001	-0.4444	0.328977
50	-0.09725	-0.8644	0.194998
51	-0.037994	-0.3377	0.368242
52	-0.033861	-0.301	0.382118
53	-0.052605	-0.4676	0.320691
54	-0.099335	-0.8829	0.189983
55	-0.009249	-0.0822	0.467345
56	-0.039045	-0.347	0.364742
57	-0.017303	-0.1538	0.439084
58	-0.079878	-0.71	0.239907
59	0.005058	0.045	0.482126
60	0.138892	1.2345	0.110339

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.125113	1.112	0.13475
2	-0.045729	-0.4064	0.342757
3	0.091196	0.8106	0.210026
4	0.122543	1.0892	0.139692
5	-0.044143	-0.3923	0.347929
6	-0.208929	-1.857	0.033519
7	0.069611	0.6187	0.268943
8	0.096926	0.8615	0.195786
9	0.082119	0.7299	0.233808
10	-0.056976	-0.5064	0.306987
11	0.019364	0.1721	0.431895
12	0.628206	5.5836	0
13	-0.201358	-1.7897	0.038666
14	-0.032095	-0.2853	0.388093
15	-0.034591	-0.3075	0.379654
16	-0.096955	-0.8618	0.195716
17	-0.000536	-0.0048	0.498104
18	-0.07897	-0.7019	0.242402
19	-0.011465	-0.1019	0.459547
20	-0.08312	-0.7388	0.231112
21	-0.023482	-0.2087	0.417605
22	0.045748	0.4066	0.342695
23	0.02057	0.1828	0.427701
24	0.125538	1.1158	0.133944
25	-0.025364	-0.2254	0.41111
26	-0.038267	-0.3401	0.367334
27	-0.073679	-0.6549	0.257225
28	-0.111806	-0.9938	0.161688
29	0.14741	1.3102	0.096961
30	0.001189	0.0106	0.495799
31	-0.207224	-1.8418	0.034625
32	0.016649	0.148	0.441368
33	-0.03668	-0.326	0.372637
34	-0.062248	-0.5533	0.290819
35	0.086784	0.7714	0.221398
36	-0.021609	-0.1921	0.424093
37	-0.052121	-0.4633	0.322225
38	-0.024995	-0.2222	0.412381
39	0.040086	0.3563	0.361286
40	0.128804	1.1448	0.127866
41	-0.068546	-0.6092	0.272055
42	-0.007224	-0.0642	0.474482
43	-0.001705	-0.0152	0.493974
44	-0.028875	-0.2567	0.399058
45	0.005987	0.0532	0.478848
46	0.066485	0.5909	0.278127
47	-0.009192	-0.0817	0.467545
48	-0.189924	-1.6881	0.04767
49	0.019451	0.1729	0.431593
50	0.005921	0.0526	0.479082
51	-0.035927	-0.3193	0.375162
52	-0.060522	-0.5379	0.296069
53	-0.024226	-0.2153	0.415033
54	0.102894	0.9145	0.181608
55	0.051524	0.458	0.324122
56	-0.06212	-0.5521	0.291206
57	0.07551	0.6711	0.252042
58	-0.04879	-0.4337	0.332861
59	-0.064786	-0.5758	0.283182
60	0.004435	0.0394	0.484328

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/09/t1273395418rczmsz621nl8krq/1v14u1273395344.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/09/t1273395418rczmsz621nl8krq/1v14u1273395344.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/09/t1273395418rczmsz621nl8krq/2v14u1273395344.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/09/t1273395418rczmsz621nl8krq/2v14u1273395344.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; 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 (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')

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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