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WERKLOOSHEID

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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: Tue, 23 Nov 2010 19:40:36 +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/Nov/23/t1290541155qqls0ivwdxlwqk7.htm/, Retrieved Tue, 23 Nov 2010 20:39:16 +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/Nov/23/t1290541155qqls0ivwdxlwqk7.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:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

8.6 8.5 8.4 8.0 7.9 8.1 8.6 8.8 8.8 8.6 8.3 8.3 8.3 8.4 8.4 8.5 8.6 8.6 8.6 8.6 8.6 8.5 8.4 8.4 8.4 8.5 8.5 8.6 8.6 8.4 8.2 8.0 8.0 8.0 8.0 7.9 7.9 7.8 7.9 8.0 7.9 7.4 7.2 7.0 7.0 7.1 7.2 7.2 7.0 6.9 6.8 6.8 6.8 6.9 7.2 7.3 7.2 7.1 7.1 7.3 7.5 7.6 7.7 7.7 7.7 7.8 8.0 8.1 8.1 8.0 8.1 8.2 8.3 8.4 8.6 8.6 8.7 8.8 8.9

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	0.514283	4.542	1e-05
2	0.028567	0.2523	0.400738
3	-0.340787	-3.0097	0.00176
4	-0.259094	-2.2883	0.012415
5	-0.047534	-0.4198	0.33789
6	0.199588	1.7627	0.040933
7	0.317293	2.8023	0.003199
8	0.218027	1.9256	0.028902
9	0.106607	0.9415	0.174671
10	0.047179	0.4167	0.339031
11	0.099837	0.8817	0.190314
12	0.105906	0.9353	0.176252
13	0.012942	0.1143	0.454648
14	-0.016101	-0.1422	0.443643
15	-0.033441	-0.2953	0.384259
16	-0.085891	-0.7586	0.225197
17	-0.085675	-0.7567	0.225766
18	-0.056199	-0.4963	0.310526
19	0.108096	0.9547	0.171346
20	0.167056	1.4754	0.072065
21	0.131711	1.1632	0.124139
22	-0.026749	-0.2362	0.406932
23	-0.184984	-1.6337	0.053172
24	-0.295954	-2.6138	0.005371
25	-0.230691	-2.0374	0.0225
26	-0.008103	-0.0716	0.471567
27	0.126708	1.1191	0.133276
28	0.03892	0.3437	0.365985
29	-0.125617	-1.1094	0.135329
30	-0.143856	-1.2705	0.103841
31	-0.033579	-0.2966	0.383794
32	0.065894	0.582	0.281134
33	0.00174	0.0154	0.493889
34	-0.056563	-0.4995	0.3094
35	-0.290872	-2.5689	0.006055
36	-0.273776	-2.4179	0.008971
37	-0.139866	-1.2353	0.110221
38	0.157672	1.3925	0.08386
39	0.186923	1.6509	0.051394
40	0.151803	1.3407	0.091956
41	-0.018811	-0.1661	0.434241
42	-0.130681	-1.1541	0.125983
43	-0.160399	-1.4166	0.08029
44	-0.143077	-1.2636	0.105064
45	-0.043379	-0.3831	0.351341
46	0.062172	0.5491	0.292256
47	0.138238	1.2209	0.112903
48	0.119774	1.0578	0.146703

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.514283	4.542	1e-05
2	-0.320757	-2.8328	0.002935
3	-0.295876	-2.6131	0.005381
4	0.15883	1.4027	0.082331
5	0.018953	0.1674	0.433747
6	0.101429	0.8958	0.186559
7	0.17131	1.513	0.067165
8	-0.024597	-0.2172	0.414296
9	0.151848	1.3411	0.091892
10	0.156599	1.383	0.085298
11	0.124488	1.0994	0.137478
12	0.049835	0.4401	0.33053
13	-0.098593	-0.8708	0.193281
14	0.092158	0.8139	0.209085
15	-0.039554	-0.3493	0.363893
16	-0.260565	-2.3012	0.012024
17	-0.054077	-0.4776	0.317136
18	-0.154639	-1.3657	0.087974
19	0.086137	0.7607	0.224553
20	0.014781	0.1305	0.448237
21	-0.104565	-0.9235	0.1793
22	0.005818	0.0514	0.479577
23	-0.079624	-0.7032	0.242005
24	-0.128218	-1.1324	0.13047
25	0.022297	0.1969	0.422202
26	0.005136	0.0454	0.48197
27	-0.02213	-0.1954	0.422775
28	-0.160068	-1.4137	0.080717
29	-0.091926	-0.8119	0.209668
30	0.149026	1.3162	0.095988
31	0.053428	0.4719	0.31917
32	0.065133	0.5752	0.283391
33	-0.080127	-0.7077	0.240631
34	0.089357	0.7892	0.216199
35	-0.228265	-2.016	0.023623
36	0.075243	0.6645	0.254155
37	0.042352	0.374	0.354694
38	0.046319	0.4091	0.341801
39	-0.059091	-0.5219	0.301616
40	0.152784	1.3494	0.090563
41	-0.066917	-0.591	0.278116
42	0.013572	0.1199	0.452448
43	0.070153	0.6196	0.268671
44	-0.028498	-0.2517	0.400973
45	-0.000806	-0.0071	0.497171
46	0.033338	0.2944	0.384604
47	0.061835	0.5461	0.293275
48	-0.026789	-0.2366	0.406796

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/23/t1290541155qqls0ivwdxlwqk7/11llq1290541233.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/23/t1290541155qqls0ivwdxlwqk7/11llq1290541233.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/23/t1290541155qqls0ivwdxlwqk7/21llq1290541233.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/23/t1290541155qqls0ivwdxlwqk7/21llq1290541233.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; 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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