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deel1 D=d=1

*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: Tue, 15 Dec 2009 13:05:42 -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/15/t12609075760oy6mqwm5qjfa92.htm/, Retrieved Tue, 15 Dec 2009 21:06:18 +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/15/t12609075760oy6mqwm5qjfa92.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 «

627 696 825 677 656 785 412 352 839 729 696 641 695 638 762 635 721 854 418 367 824 687 601 676 740 691 683 594 729 731 386 331 707 715 657 653 642 643 718 654 632 731 392 344 792 852 649 629 685 617 715 715 629 916 531 357 917 828 708 858 775 785 1006 789 734 906 532 387 991 841

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	-0.295836	-2.2335	0.014728
2	-0.197857	-1.4938	0.070374
3	0.09632	0.7272	0.23504
4	-0.275432	-2.0795	0.021042
5	0.218357	1.6486	0.05237
6	0.058248	0.4398	0.330885
7	-0.24291	-1.8339	0.035943
8	0.18512	1.3976	0.08382
9	0.070651	0.5334	0.297915
10	-0.056402	-0.4258	0.33592
11	0.151632	1.1448	0.128539
12	-0.238536	-1.8009	0.038504
13	-0.075803	-0.5723	0.284685
14	0.120933	0.913	0.182539
15	0.008246	0.0623	0.475289
16	-0.004827	-0.0364	0.485528
17	0.053514	0.404	0.343855
18	-0.023404	-0.1767	0.430186
19	-0.113175	-0.8545	0.198216
20	0.181624	1.3712	0.087839
21	-0.035971	-0.2716	0.393465
22	-0.079351	-0.5991	0.275745
23	0.087005	0.6569	0.256953
24	-0.162354	-1.2257	0.112668
25	0.051016	0.3852	0.350776
26	0.085683	0.6469	0.260148
27	-0.101899	-0.7693	0.222439
28	0.041655	0.3145	0.377148
29	0.095166	0.7185	0.237697
30	-0.090123	-0.6804	0.249499
31	0.07358	0.5555	0.290358
32	-0.184159	-1.3904	0.084911
33	-0.009446	-0.0713	0.471697
34	0.117844	0.8897	0.188682
35	-0.022676	-0.1712	0.432337
36	0.015127	0.1142	0.454737
37	0.036428	0.275	0.392147
38	-0.010994	-0.083	0.46707
39	0.026339	0.1989	0.421543
40	-0.07349	-0.5548	0.290587
41	-0.104463	-0.7887	0.216784
42	0.074424	0.5619	0.288199
43	0.065782	0.4966	0.310674
44	0.014563	0.1099	0.456418
45	0.005643	0.0426	0.483084
46	-0.058761	-0.4436	0.329492
47	0.011639	0.0879	0.465144
48	-0.003232	-0.0244	0.490309
49	-0.054937	-0.4148	0.339935
50	0.047658	0.3598	0.36016
51	0.007776	0.0587	0.476695
52	0.031022	0.2342	0.407829
53	-0.010887	-0.0822	0.46739
54	-0.025821	-0.1949	0.423065
55	0.008519	0.0643	0.474471
56	0.011233	0.0848	0.466356
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.295836	-2.2335	0.014728
2	-0.312747	-2.3612	0.010829
3	-0.088726	-0.6699	0.252825
4	-0.404405	-3.0532	0.001719
5	-0.043407	-0.3277	0.372164
6	-0.06826	-0.5153	0.304151
7	-0.254902	-1.9245	0.029646
8	-0.080667	-0.609	0.272465
9	0.083954	0.6338	0.26436
10	0.065089	0.4914	0.312511
11	0.207529	1.5668	0.061347
12	0.03142	0.2372	0.406671
13	-0.031428	-0.2373	0.406646
14	-0.075979	-0.5736	0.284238
15	0.044135	0.3332	0.370099
16	-0.113895	-0.8599	0.196726
17	-0.01684	-0.1271	0.44964
18	0.035923	0.2712	0.393605
19	-0.218612	-1.6505	0.052172
20	0.055075	0.4158	0.339555
21	0.120938	0.9131	0.182529
22	0.072935	0.5506	0.292015
23	0.137878	1.041	0.151146
24	0.007359	0.0556	0.477945
25	-0.060564	-0.4573	0.324614
26	-0.13491	-1.0186	0.15636
27	-0.072819	-0.5498	0.292311
28	-0.186166	-1.4055	0.082646
29	-0.020715	-0.1564	0.438136
30	0.003474	0.0262	0.489583
31	-0.025666	-0.1938	0.423522
32	-0.212662	-1.6056	0.056949
33	0.006524	0.0493	0.480446
34	-0.052504	-0.3964	0.346646
35	0.010227	0.0772	0.469362
36	-0.043637	-0.3295	0.37151
37	0.013837	0.1045	0.458582
38	-0.049078	-0.3705	0.356181
39	0.086847	0.6557	0.257335
40	-0.061184	-0.4619	0.322946
41	-0.099555	-0.7516	0.227686
42	-0.001112	-0.0084	0.496666
43	0.032874	0.2482	0.402439
44	-0.071446	-0.5394	0.295855
45	0.037821	0.2855	0.388133
46	-0.020883	-0.1577	0.43764
47	-0.003195	-0.0241	0.49042
48	-0.044331	-0.3347	0.369543
49	-0.071054	-0.5364	0.296868
50	-0.031635	-0.2388	0.406042
51	-0.012025	-0.0908	0.463991
52	0.065479	0.4944	0.311476
53	-0.045727	-0.3452	0.365594
54	-0.014919	-0.1126	0.455359
55	0.032183	0.243	0.404448
56	-0.039673	-0.2995	0.382815
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/15/t12609075760oy6mqwm5qjfa92/1x1yi1260907540.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12609075760oy6mqwm5qjfa92/1x1yi1260907540.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12609075760oy6mqwm5qjfa92/2cc001260907540.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12609075760oy6mqwm5qjfa92/2cc001260907540.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = -0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = -0.5 ; par3 = 1 ; par4 = 1 ; 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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