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auto corr nd cons

*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: Fri, 19 Dec 2008 04:02:29 -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/19/t1229684631ywlnq0ppya2fb0j.htm/, Retrieved Fri, 19 Dec 2008 12:03:56 +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/2008/Dec/19/t1229684631ywlnq0ppya2fb0j.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

95,9 95,3 100,4 97,3 82,3 97,0 93,5 90,9 107,8 110,9 98,1 106,5 93,4 95,7 109,0 97,6 92,7 107,5 91,7 95,7 111,4 106,0 104,8 108,7 97,3 97,1 106,1 98,6 98,5 105,5 86,2 98,3 111,3 105,0 105,7 103,5 96,9 98,1 111,7 94,7 104,2 109,7 91,3 102,6 114,2 115,8 113,5 107,1 104,5 101,9 116,0 102,0 108,1 112,9 104,5 109,1 113,4 123,9 117,7 108,3

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	0.33001	2.5562	0.006565
2	0.148336	1.149	0.127557
3	0.376387	2.9155	0.002494
4	0.002691	0.0208	0.491721
5	0.100792	0.7807	0.219016
6	0.391811	3.035	0.001777
7	0.032867	0.2546	0.399955
8	0.003655	0.0283	0.488754
9	0.249056	1.9292	0.029221
10	-0.069642	-0.5394	0.295788
11	0.166745	1.2916	0.100724
12	0.571045	4.4233	2.1e-05
13	0.069075	0.535	0.297297
14	0.024963	0.1934	0.423663
15	0.082012	0.6353	0.263837
16	-0.214242	-1.6595	0.051116
17	-0.035581	-0.2756	0.391896
18	0.145974	1.1307	0.131338
19	-0.123225	-0.9545	0.171832
20	-0.08051	-0.6236	0.267619
21	0.051239	0.3969	0.346427
22	-0.17691	-1.3703	0.087843
23	0.086237	0.668	0.253352
24	0.273091	2.1154	0.01928
25	-0.024153	-0.1871	0.426112
26	-0.008214	-0.0636	0.474741
27	-0.029534	-0.2288	0.409912
28	-0.228982	-1.7737	0.040595
29	-0.049685	-0.3849	0.350852
30	0.045664	0.3537	0.362397
31	-0.112276	-0.8697	0.193969
32	-0.050716	-0.3928	0.347914
33	-0.024609	-0.1906	0.424734
34	-0.14437	-1.1183	0.133951
35	0.059111	0.4579	0.324349
36	0.123955	0.9602	0.170416
37	-0.046579	-0.3608	0.359758
38	-0.071508	-0.5539	0.290853
39	-0.107917	-0.8359	0.203259
40	-0.22466	-1.7402	0.043475
41	-0.153081	-1.1858	0.120197
42	-0.10929	-0.8466	0.200302
43	-0.140185	-1.0859	0.140941
44	-0.113349	-0.878	0.191723
45	-0.133488	-1.034	0.152644
46	-0.154891	-1.1998	0.117471
47	-0.056998	-0.4415	0.330219
48	-0.025104	-0.1945	0.423239
49	-0.073924	-0.5726	0.284522
50	-0.117464	-0.9099	0.183264
51	-0.151414	-1.1728	0.122747
52	-0.17198	-1.3321	0.093925
53	-0.181309	-1.4044	0.082676
54	-0.134033	-1.0382	0.151667
55	-0.093597	-0.725	0.235635
56	-0.081195	-0.6289	0.26589
57	-0.073878	-0.5723	0.284643
58	-0.037213	-0.2882	0.387075
59	-0.009009	-0.0698	0.472299
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.33001	2.5562	0.006565
2	0.044248	0.3427	0.366494
3	0.35419	2.7435	0.004002
4	-0.279005	-2.1612	0.017342
5	0.222142	1.7207	0.045229
6	0.227464	1.7619	0.041588
7	-0.13689	-1.0603	0.146619
8	-0.069742	-0.5402	0.295523
9	0.142075	1.1005	0.137754
10	-0.119076	-0.9224	0.180018
11	0.315258	2.442	0.008786
12	0.361209	2.7979	0.003452
13	-0.255995	-1.9829	0.025979
14	-0.161273	-1.2492	0.108219
15	-0.285841	-2.2141	0.015316
16	0.056014	0.4339	0.332965
17	-0.029908	-0.2317	0.408793
18	-0.037997	-0.2943	0.384764
19	0.034779	0.2694	0.394273
20	-0.049317	-0.382	0.351903
21	0.050949	0.3947	0.347249
22	0.070902	0.5492	0.292451
23	0.04523	0.3504	0.36365
24	-0.086044	-0.6665	0.253825
25	0.02202	0.1706	0.43257
26	-0.045873	-0.3553	0.361795
27	0.085404	0.6615	0.255402
28	-0.06004	-0.4651	0.321783
29	0.001319	0.0102	0.495942
30	-0.061318	-0.475	0.318267
31	0.043675	0.3383	0.368157
32	-0.011454	-0.0887	0.464798
33	-0.011167	-0.0865	0.465679
34	-0.007306	-0.0566	0.477529
35	-0.046808	-0.3626	0.359098
36	-0.012315	-0.0954	0.462162
37	-0.041336	-0.3202	0.374969
38	-0.112052	-0.868	0.19444
39	0.019874	0.1539	0.439086
40	-0.042176	-0.3267	0.372519
41	-0.12806	-0.9919	0.162603
42	-0.085785	-0.6645	0.254462
43	0.068216	0.5284	0.299586
44	0.011881	0.092	0.463489
45	-0.032438	-0.2513	0.401236
46	-0.038991	-0.302	0.381839
47	-0.024204	-0.1875	0.425957
48	-0.048696	-0.3772	0.353679
49	0.051868	0.4018	0.344643
50	0.032326	0.2504	0.401569
51	-0.042056	-0.3258	0.372867
52	-0.014419	-0.1117	0.45572
53	-0.044633	-0.3457	0.36538
54	0.055981	0.4336	0.333057
55	-0.037074	-0.2872	0.387483
56	0.035044	0.2714	0.393489
57	-0.010322	-0.08	0.46827
58	0.025533	0.1978	0.421945
59	0.048571	0.3762	0.354036
60	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684631ywlnq0ppya2fb0j/1hyl81229684548.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684631ywlnq0ppya2fb0j/1hyl81229684548.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684631ywlnq0ppya2fb0j/2oey91229684548.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684631ywlnq0ppya2fb0j/2oey91229684548.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 2.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 2.0 ; par3 = 0 ; par4 = 0 ; 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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