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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: Sun, 21 Dec 2008 11:02:12 -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/21/t1229882568kquchf1519695fv.htm/, Retrieved Sun, 21 Dec 2008 19:02:48 +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/21/t1229882568kquchf1519695fv.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 «

10244 10511 10812 10738 10171 9721 9897 9828 9924 10371 10846 10413 10709 10662 10570 10297 10635 10872 10296 10383 10431 10574 10653 10805 10872 10625 10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032

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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.020197	0.1551	0.438622
2	-0.079338	-0.6094	0.272298
3	0.226551	1.7402	0.043522
4	0.05205	0.3998	0.345373
5	-0.291641	-2.2401	0.014431
6	0.006479	0.0498	0.480239
7	0.255647	1.9637	0.027144
8	-0.113601	-0.8726	0.193213
9	-0.102377	-0.7864	0.217397
10	0.051144	0.3928	0.347924
11	0.047818	0.3673	0.357356
12	-0.222249	-1.7071	0.046529
13	-0.034235	-0.263	0.396747
14	0.104206	0.8004	0.213338
15	-0.062341	-0.4789	0.316907
16	-0.215774	-1.6574	0.051375
17	-0.032275	-0.2479	0.402532
18	-0.036102	-0.2773	0.391258
19	-0.054398	-0.4178	0.338792
20	-0.028277	-0.2172	0.414402
21	0.114678	0.8809	0.190984
22	0.086229	0.6623	0.255166
23	-0.103495	-0.795	0.21491
24	-0.092107	-0.7075	0.241024
25	0.174791	1.3426	0.092273
26	-0.125365	-0.9629	0.169752
27	-0.050184	-0.3855	0.350639
28	0.156963	1.2057	0.116382
29	0.069142	0.5311	0.298674
30	-0.11022	-0.8466	0.200314
31	-0.07314	-0.5618	0.28819
32	0.112725	0.8659	0.195037
33	-0.213802	-1.6422	0.05293
34	-0.060957	-0.4682	0.320676
35	0.052071	0.4	0.345314
36	0.005228	0.0402	0.484051
37	-0.159637	-1.2262	0.112499
38	0.086022	0.6607	0.255673
39	0.104044	0.7992	0.213697
40	-0.041796	-0.321	0.374658
41	0.072838	0.5595	0.288975
42	0.085574	0.6573	0.256771
43	-0.009453	-0.0726	0.47118
44	-0.052094	-0.4001	0.34525
45	-0.019747	-0.1517	0.439978
46	-0.046956	-0.3607	0.359814
47	-0.032243	-0.2477	0.402626
48	0.014885	0.1143	0.454681
49	0.068172	0.5236	0.301246
50	0.052297	0.4017	0.344679
51	0.024967	0.1918	0.424289
52	0.019279	0.1481	0.441389
53	-0.031253	-0.2401	0.405559
54	-0.062583	-0.4807	0.316249
55	-0.0349	-0.2681	0.394788
56	0.00493	0.0379	0.484962
57	0.017102	0.1314	0.447967
58	0.006513	0.05	0.480136
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.020197	0.1551	0.438622
2	-0.079778	-0.6128	0.271186
3	0.231459	1.7779	0.040289
4	0.033532	0.2576	0.398819
5	-0.2739	-2.1039	0.019831
6	-0.021323	-0.1638	0.43523
7	0.240011	1.8436	0.035136
8	-0.013892	-0.1067	0.457693
9	-0.08979	-0.6897	0.246547
10	-0.145507	-1.1177	0.134122
11	0.085088	0.6536	0.257963
12	-0.057024	-0.438	0.33149
13	-0.055473	-0.4261	0.335795
14	-0.024048	-0.1847	0.427043
15	0.012723	0.0977	0.46124
16	-0.163736	-1.2577	0.106731
17	-0.138942	-1.0672	0.145107
18	-0.091287	-0.7012	0.24297
19	0.173037	1.3291	0.094462
20	0.000306	0.0023	0.499068
21	-0.031668	-0.2432	0.404328
22	0.007496	0.0576	0.477138
23	-0.02095	-0.1609	0.436353
24	-0.130373	-1.0014	0.160358
25	0.164212	1.2613	0.106076
26	-0.139547	-1.0719	0.14407
27	0.077462	0.595	0.277059
28	-0.042657	-0.3277	0.372167
29	0.017326	0.1331	0.447289
30	-0.032165	-0.2471	0.402859
31	-0.113596	-0.8726	0.193223
32	-0.015676	-0.1204	0.452283
33	-0.155448	-1.194	0.118624
34	-0.029743	-0.2285	0.410039
35	-0.015934	-0.1224	0.451503
36	-0.072966	-0.5605	0.288644
37	-0.029737	-0.2284	0.410058
38	0.080276	0.6166	0.269933
39	0.035106	0.2697	0.394185
40	0.045685	0.3509	0.363452
41	0.051704	0.3971	0.346347
42	-0.057202	-0.4394	0.330996
43	-0.002315	-0.0178	0.492935
44	-0.017267	-0.1326	0.44747
45	-0.07379	-0.5668	0.286502
46	-0.064706	-0.497	0.310511
47	-0.097784	-0.7511	0.227792
48	0.028084	0.2157	0.414975
49	-0.000607	-0.0047	0.498148
50	-0.016936	-0.1301	0.448469
51	0.030593	0.235	0.407514
52	0.009565	0.0735	0.47084
53	-0.051468	-0.3953	0.347011
54	-0.076668	-0.5889	0.279088
55	-0.035625	-0.2736	0.392659
56	0.137176	1.0537	0.148166
57	-0.029122	-0.2237	0.411885
58	0.043152	0.3315	0.370736
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229882568kquchf1519695fv/12e131229882526.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229882568kquchf1519695fv/12e131229882526.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229882568kquchf1519695fv/2mogq1229882526.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229882568kquchf1519695fv/2mogq1229882526.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 60 ; par2 = -0.8 ; par3 = 1 ; 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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