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paper

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Wed, 17 Dec 2008 13:32:46 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/17/t122954600199u2a0moqdueljp.htm/, Retrieved Wed, 17 Dec 2008 21:33:23 +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/2008/Dec/17/t122954600199u2a0moqdueljp.htm/},
    year = {2008},
}
@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 = {2008},
    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:

Van Dooren Leen

Dataseries X:

» Textbox « » Textfile « » CSV «

98.6 98.0 106.8 96.6 100.1 107.7 91.5 97.8 107.4 117.5 105.6 97.4 99.5 98.0 104.3 100.6 101.1 103.9 96.9 95.5 108.4 117.0 103.8 100.8 110.6 104.0 112.6 107.3 98.9 109.8 104.9 102.2 123.9 124.9 112.7 121.9 100.6 104.3 120.4 107.5 102.9 125.6 107.5 108.8 128.4 121.1 119.5 128.7 108.7 105.5 119.8 111.3 110.6 120.1 97.5 107.7 127.3 117.2 119.8 116.2 111.0 112.4 130.6 109.1 118.8 123.9 101.6 112.8 128.0 129.6 125.8 119.5 115.7 113.6 129.7 112.0 116.8 127.0 112.1 114.2 121.1 131.6 125.0 120.4 117.7 117.5 120.6 127.5 112.3 124.5 115.2 104.7 130.5

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' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.018193	0.1637	0.435173
2	0.084647	0.7618	0.22419
3	0.251445	2.263	0.013156
4	-0.087743	-0.7897	0.216009
5	0.119633	1.0767	0.142406
6	0.180448	1.624	0.054127
7	-0.120495	-1.0845	0.14069
8	0.098281	0.8845	0.189514
9	0.229171	2.0625	0.021181
10	-0.168149	-1.5133	0.067043
11	-0.056964	-0.5127	0.304785
12	-0.151676	-1.3651	0.088003
13	-0.235807	-2.1223	0.018435
14	0.083968	0.7557	0.226008
15	-0.066182	-0.5956	0.276539
16	-0.139713	-1.2574	0.106109
17	0.158337	1.425	0.078995
18	-0.090994	-0.8189	0.20761
19	-0.211917	-1.9073	0.030016
20	-0.002684	-0.0242	0.490395
21	-0.062226	-0.56	0.288501
22	-0.139637	-1.2567	0.106231
23	0.177948	1.6015	0.056577
24	-0.269178	-2.4226	0.00882
25	-0.089722	-0.8075	0.210872
26	0.0417	0.3753	0.354209
27	-0.035424	-0.3188	0.375342
28	-0.079296	-0.7137	0.238743
29	0.008677	0.0781	0.468972
30	-0.020495	-0.1845	0.427057
31	0.06841	0.6157	0.269914
32	0.133247	1.1992	0.11697
33	-0.153181	-1.3786	0.085902
34	0.039092	0.3518	0.362942
35	0.105867	0.9528	0.171763
36	0.047746	0.4297	0.334273
37	0.209946	1.8895	0.0312
38	0.069287	0.6236	0.267327
39	-0.060005	-0.54	0.295323
40	0.106249	0.9562	0.170898
41	-0.006564	-0.0591	0.476517
42	-0.082053	-0.7385	0.231181
43	0.059456	0.5351	0.297021
44	0.056763	0.5109	0.305418
45	-0.094446	-0.85	0.198912
46	0.137243	1.2352	0.110166
47	-0.086915	-0.7822	0.218179
48	-0.149677	-1.3471	0.090854
49	-0.004999	-0.045	0.482112
50	-0.121876	-1.0969	0.137972
51	-0.116793	-1.0511	0.14816
52	0.088737	0.7986	0.213418
53	-0.068205	-0.6138	0.27052
54	-0.034721	-0.3125	0.377737
55	0.038884	0.35	0.363638
56	-0.201407	-1.8127	0.036794
57	-0.018489	-0.1664	0.434129
58	-0.002432	-0.0219	0.491297
59	-0.087948	-0.7915	0.215472
60	0.041796	0.3762	0.353888

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.018193	0.1637	0.435173
2	0.084343	0.7591	0.225001
3	0.250364	2.2533	0.013472
4	-0.105298	-0.9477	0.173055
5	0.086994	0.7829	0.217972
6	0.141496	1.2735	0.103248
7	-0.106933	-0.9624	0.169356
8	0.023879	0.2149	0.415188
9	0.218356	1.9652	0.026409
10	-0.147409	-1.3267	0.09417
11	-0.19837	-1.7853	0.038975
12	-0.22179	-1.9961	0.024641
13	-0.113152	-1.0184	0.155768
14	0.08234	0.7411	0.230399
15	0.0065	0.0585	0.476747
16	-0.011004	-0.099	0.460677
17	0.173461	1.5611	0.061194
18	-0.025078	-0.2257	0.411001
19	-0.212989	-1.9169	0.029388
20	-0.055248	-0.4972	0.310187
21	0.202783	1.825	0.03584
22	-0.115713	-1.0414	0.15039
23	-0.02016	-0.1814	0.428239
24	-0.308725	-2.7785	0.003392
25	-0.091575	-0.8242	0.206131
26	-0.114428	-1.0298	0.153073
27	0.283562	2.5521	0.006294
28	0.063312	0.5698	0.285193
29	0.075933	0.6834	0.248154
30	-0.028102	-0.2529	0.400487
31	-0.018149	-0.1633	0.435328
32	-0.008448	-0.076	0.469792
33	0.008747	0.0787	0.468725
34	0.018649	0.1678	0.433563
35	0.059814	0.5383	0.295913
36	-0.047463	-0.4272	0.335194
37	0.021123	0.1901	0.424852
38	-0.047105	-0.4239	0.336364
39	-0.017287	-0.1556	0.438373
40	-0.053871	-0.4848	0.314551
41	0.074345	0.6691	0.252664
42	0.029099	0.2619	0.397034
43	-0.013278	-0.1195	0.452586
44	-0.080344	-0.7231	0.235853
45	-0.101358	-0.9122	0.182179
46	0.010725	0.0965	0.461672
47	0.077417	0.6967	0.243977
48	-0.149402	-1.3446	0.09125
49	0.003718	0.0335	0.486695
50	-0.059701	-0.5373	0.296265
51	-0.024519	-0.2207	0.412951
52	-0.032488	-0.2924	0.385369
53	0.020099	0.1809	0.428451
54	0.037123	0.3341	0.369582
55	0.054376	0.4894	0.312945
56	-0.043278	-0.3895	0.348965
57	-0.046106	-0.415	0.339635
58	-0.122473	-1.1023	0.136806
59	0.04147	0.3732	0.354975
60	0.022736	0.2046	0.419191

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t122954600199u2a0moqdueljp/1rksf1229545963.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t122954600199u2a0moqdueljp/1rksf1229545963.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t122954600199u2a0moqdueljp/2nrsi1229545963.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t122954600199u2a0moqdueljp/2nrsi1229545963.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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