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acf 2 hooggeschoolden

*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: Wed, 22 Dec 2010 14:30:09 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/22/t129302808385spdivf15t9z1p.htm/, Retrieved Wed, 22 Dec 2010 15:28:05 +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/2010/Dec/22/t129302808385spdivf15t9z1p.htm/},
    year = {2010},
}
@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 = {2010},
    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 «

19246 17549 16428 16209 15235 16186 24971 30776 26416 23157 20155 19790 18849 17573 16597 16158 15507 16433 26325 31144 30535 27596 24064 23854 22407 21125 20226 19547 18933 20372 34331 37329 36761 32737 29321 28883 27436 25101 23776 23782 23027 25606 41328 44751 42855 37628 33544 33275 32009 30813 29143 28121 27007 29112 44067 48481 46581 41166 36824 35936 33633 31630 30434 28546 27660 29830 45599 49303 44417 40386 35544 35019 30400 29602 27701 27937 27283 29372 42821 45386 40170 34371 30077 29251 27202 25714 23784 22968 22243 24255 37282 38794 31828 27949 24605 25695 23338 21941 22034 20637 19418 22454 33261 34995 29132 26171 23828 25743 25204 25679 25281 25136 24794 28278 40062 42590 37885 34061 32412 34647 31750 31288 29331 28768 27780 30113 41240 43271 38108 34382 31551

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	-0.003121	-0.0339	0.486505
2	0.154939	1.6831	0.047503
3	-0.059193	-0.643	0.260734
4	0.040918	0.4445	0.328753
5	-0.002457	-0.0267	0.489378
6	-0.034102	-0.3704	0.35586
7	0.051546	0.5599	0.288292
8	-0.036908	-0.4009	0.3446
9	0.112334	1.2203	0.1124
10	0.144123	1.5656	0.060063
11	0.088674	0.9632	0.168698
12	-0.088884	-0.9655	0.168129
13	0.058302	0.6333	0.263875
14	-0.024697	-0.2683	0.394477
15	-0.070803	-0.7691	0.221679
16	-0.182546	-1.983	0.024848
17	-0.126936	-1.3789	0.08527
18	0.027556	0.2993	0.382606
19	-0.016605	-0.1804	0.428585
20	0.07977	0.8665	0.19398
21	-0.006131	-0.0666	0.473507
22	0.014577	0.1583	0.437227
23	-0.016147	-0.1754	0.430534
24	-0.01066	-0.1158	0.454006
25	-0.066681	-0.7243	0.235146
26	-0.124542	-1.3529	0.089342
27	-0.116647	-1.2671	0.103804
28	0.040206	0.4367	0.331546
29	-0.018708	-0.2032	0.419658
30	-0.087138	-0.9466	0.172899
31	-0.082053	-0.8913	0.187285
32	0.030886	0.3355	0.368917
33	-0.076377	-0.8297	0.204202
34	0.076992	0.8363	0.202325
35	0.052985	0.5756	0.283003
36	-0.056175	-0.6102	0.271445
37	-0.07476	-0.8121	0.209185
38	-0.179934	-1.9546	0.026499
39	0.050849	0.5524	0.290872
40	-0.090285	-0.9808	0.164361
41	0.047026	0.5108	0.305212
42	-0.027254	-0.2961	0.383854
43	0.065326	0.7096	0.23967
44	-0.063186	-0.6864	0.246912
45	0.058788	0.6386	0.26216
46	0.034004	0.3694	0.356255
47	-0.068822	-0.7476	0.228095
48	-0.116051	-1.2606	0.104963

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.003121	-0.0339	0.486505
2	0.154931	1.683	0.047511
3	-0.059736	-0.6489	0.258834
4	0.017628	0.1915	0.424238
5	0.016003	0.1738	0.431146
6	-0.048041	-0.5219	0.301375
7	0.055337	0.6011	0.27446
8	-0.026303	-0.2857	0.387794
9	0.094396	1.0254	0.153635
10	0.167756	1.8223	0.035471
11	0.052206	0.5671	0.285861
12	-0.130299	-1.4154	0.079791
13	0.057483	0.6244	0.266776
14	-0.000121	-0.0013	0.499476
15	-0.104911	-1.1396	0.128376
16	-0.18001	-1.9554	0.026449
17	-0.124708	-1.3547	0.089055
18	0.067633	0.7347	0.231997
19	-0.002905	-0.0316	0.487441
20	0.006505	0.0707	0.471893
21	0.017485	0.1899	0.424845
22	0.027649	0.3003	0.382221
23	-0.00313	-0.034	0.486466
24	-0.022138	-0.2405	0.405189
25	-0.011792	-0.1281	0.449144
26	-0.033241	-0.3611	0.359338
27	-0.089835	-0.9759	0.165566
28	0.037443	0.4067	0.34247
29	-0.010275	-0.1116	0.45566
30	-0.122251	-1.328	0.093373
31	-0.136634	-1.4842	0.070208
32	0.018688	0.203	0.419741
33	-0.102394	-1.1123	0.134138
34	0.090313	0.9811	0.164287
35	0.14722	1.5992	0.056223
36	-0.02131	-0.2315	0.408668
37	-0.042639	-0.4632	0.322046
38	-0.214008	-2.3247	0.010898
39	0.042886	0.4659	0.321085
40	0.047427	0.5152	0.303693
41	-0.006438	-0.0699	0.47218
42	-0.079737	-0.8662	0.194079
43	0.035279	0.3832	0.351121
44	-0.079558	-0.8642	0.194611
45	-0.001956	-0.0213	0.49154
46	0.04215	0.4579	0.323944
47	-0.073675	-0.8003	0.212567
48	-0.153594	-1.6685	0.048938

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/22/t129302808385spdivf15t9z1p/1fn1w1293028207.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/22/t129302808385spdivf15t9z1p/1fn1w1293028207.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/22/t129302808385spdivf15t9z1p/2fn1w1293028207.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/22/t129302808385spdivf15t9z1p/2fn1w1293028207.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; 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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