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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: Mon, 28 Dec 2009 12:57:26 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/28/t1262030398kt08x1xeaxoglo0.htm/, Retrieved Mon, 28 Dec 2009 21:00:00 +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/2009/Dec/28/t1262030398kt08x1xeaxoglo0.htm/},
    year = {2009},
}
@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 = {2009},
    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 «

2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.1 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.4 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.4 3857.62 3801.06 3504.37 3032.6 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41 1810.99 1670.07 1864.44 2052.02 2029.6 2070.83 2293.41 2443.27 2513.17 2466.92

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.293367	2.2534	0.013982
2	0.07764	0.5964	0.276606
3	0.222185	1.7066	0.046574
4	0.240563	1.8478	0.034823
5	0.252465	1.9392	0.028631
6	-0.040352	-0.31	0.378845
7	-0.051907	-0.3987	0.345775
8	0.141785	1.0891	0.140275
9	0.024364	0.1871	0.426095
10	-0.169302	-1.3004	0.099255
11	0.114639	0.8806	0.191065
12	-0.012426	-0.0954	0.462142
13	-0.039393	-0.3026	0.381635
14	0.048817	0.375	0.354514
15	-0.058522	-0.4495	0.327353
16	0.042946	0.3299	0.371331
17	-0.124097	-0.9532	0.172186
18	-0.170674	-1.311	0.097473
19	0.018037	0.1385	0.445142
20	-0.09558	-0.7342	0.232879
21	-0.170992	-1.3134	0.097064
22	-0.177413	-1.3627	0.089073
23	-0.159168	-1.2226	0.113173
24	-0.116244	-0.8929	0.187773
25	-0.07093	-0.5448	0.293964
26	-0.123643	-0.9497	0.173065
27	-0.029967	-0.2302	0.409374
28	0.053575	0.4115	0.341092
29	-0.034815	-0.2674	0.395039
30	-0.037619	-0.289	0.386814
31	-0.079569	-0.6112	0.271714
32	-0.020117	-0.1545	0.438863
33	-0.039693	-0.3049	0.380761
34	-0.090533	-0.6954	0.244768
35	-0.115249	-0.8852	0.189808
36	-0.044641	-0.3429	0.366447
37	-0.007423	-0.057	0.477363
38	-0.03327	-0.2555	0.399594
39	-0.053953	-0.4144	0.340035
40	-0.04658	-0.3578	0.360889
41	0.012655	0.0972	0.461446
42	0.015103	0.116	0.454019
43	0.023598	0.1813	0.428394
44	-0.007077	-0.0544	0.478416
45	0.004028	0.0309	0.48771
46	0.01268	0.0974	0.461372
47	0.001548	0.0119	0.495275
48	0.007419	0.057	0.477375
49	0.014518	0.1115	0.455793
50	0.023943	0.1839	0.427358
51	0.017469	0.1342	0.446859
52	0.005961	0.0458	0.481816
53	0.005174	0.0397	0.484218
54	0.01966	0.151	0.44024
55	0.018341	0.1409	0.444222
56	0.009437	0.0725	0.471231
57	0.000632	0.0049	0.498072
58	-0.0014	-0.0108	0.495729
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.293367	2.2534	0.013982
2	-0.009218	-0.0708	0.471897
3	0.220934	1.697	0.047481
4	0.132651	1.0189	0.156202
5	0.174699	1.3419	0.092387
6	-0.217285	-1.669	0.050209
7	-0.057807	-0.444	0.329325
8	0.072663	0.5581	0.289431
9	-0.061318	-0.471	0.319691
10	-0.172441	-1.3245	0.095216
11	0.308195	2.3673	0.010609
12	-0.179998	-1.3826	0.086001
13	0.019872	0.1526	0.439602
14	0.110028	0.8451	0.200724
15	-0.056897	-0.437	0.33184
16	-0.092939	-0.7139	0.239058
17	-0.091982	-0.7065	0.241322
18	-0.060666	-0.466	0.321472
19	-0.006218	-0.0478	0.481034
20	-0.087256	-0.6702	0.252663
21	0.063378	0.4868	0.314096
22	-0.206877	-1.5891	0.058696
23	-0.0011	-0.0084	0.496644
24	-0.045473	-0.3493	0.36406
25	0.053615	0.4118	0.340979
26	0.003095	0.0238	0.490557
27	0.053824	0.4134	0.340395
28	0.106182	0.8156	0.209005
29	-0.025131	-0.193	0.423797
30	-0.162629	-1.2492	0.108267
31	0.015974	0.1227	0.451382
32	-0.090504	-0.6952	0.244837
33	-0.084261	-0.6472	0.259999
34	0.009897	0.076	0.469831
35	-0.034761	-0.267	0.395199
36	0.022455	0.1725	0.431825
37	0.040923	0.3143	0.377187
38	0.071933	0.5525	0.291338
39	-0.141722	-1.0886	0.140382
40	-0.064896	-0.4985	0.31
41	0.013468	0.1035	0.458978
42	-0.051069	-0.3923	0.348137
43	0.022968	0.1764	0.430284
44	0.015715	0.1207	0.452166
45	-0.02366	-0.1817	0.428208
46	-0.011574	-0.0889	0.464731
47	-0.05012	-0.385	0.350819
48	0.01651	0.1268	0.449757
49	0.016223	0.1246	0.450627
50	0.04122	0.3166	0.376326
51	0.015846	0.1217	0.45177
52	-0.033316	-0.2559	0.399457
53	-0.048727	-0.3743	0.354768
54	-0.038271	-0.294	0.384909
55	-0.034485	-0.2649	0.39601
56	-0.056396	-0.4332	0.333229
57	-0.090805	-0.6975	0.244118
58	0.067853	0.5212	0.302093
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262030398kt08x1xeaxoglo0/1y0vu1262030243.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262030398kt08x1xeaxoglo0/1y0vu1262030243.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262030398kt08x1xeaxoglo0/2pgz71262030243.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262030398kt08x1xeaxoglo0/2pgz71262030243.ps (open in new window)

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 0.9 ; par3 = 1 ; 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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