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Identifying Integration Processes 3

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Wed, 16 Dec 2009 13:20:13 -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/16/t1260994862lyz33msjxh1ry5i.htm/, Retrieved Wed, 16 Dec 2009 21:21:04 +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/16/t1260994862lyz33msjxh1ry5i.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 «

103.34 102.60 100.69 105.67 123.61 113.08 106.46 123.38 109.87 95.74 123.06 123.39 120.28 115.33 110.40 114.49 132.03 123.16 118.82 128.32 112.24 104.53 132.57 122.52 131.80 124.55 120.96 122.60 145.52 118.57 134.25 136.70 121.37 111.63 134.42 137.65 137.86 119.77 130.69 128.28 147.45 128.42 136.90 143.95 135.64 122.48 136.83 153.04 142.71 123.46 144.37 146.15 147.61 158.51 147.40 165.05 154.64 126.20 157.36 154.15 123.21 113.07 110.45 113.57 122.44 114.93 111.85 126.04 121.34 124.36

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	-0.446026	-3.3674	0.000682
2	0.033375	0.252	0.400984
3	0.350734	2.648	0.005227
4	-0.353701	-2.6704	0.004928
5	0.127343	0.9614	0.170201
6	0.18319	1.3831	0.086021
7	-0.426036	-3.2165	0.00107
8	0.247585	1.8692	0.033366
9	-0.156434	-1.181	0.121244
10	-0.139594	-1.0539	0.148185
11	0.151132	1.141	0.129317
12	-0.141062	-1.065	0.145685
13	-0.021176	-0.1599	0.436773
14	0.124491	0.9399	0.17562
15	-0.054763	-0.4135	0.340413
16	-0.063424	-0.4788	0.316943
17	0.10472	0.7906	0.216222
18	-0.044126	-0.3331	0.370125
19	-0.066136	-0.4993	0.309738
20	0.17865	1.3488	0.091372
21	-0.114843	-0.867	0.194777
22	-0.143074	-1.0802	0.142305
23	0.323933	2.4456	0.008785
24	-0.297778	-2.2482	0.014225
25	0.117319	0.8857	0.189739
26	0.123164	0.9299	0.178181
27	-0.174963	-1.3209	0.0959
28	0.097609	0.7369	0.232094
29	0.052884	0.3993	0.345595
30	-0.150985	-1.1399	0.129545
31	0.155591	1.1747	0.122503
32	-0.10224	-0.7719	0.221683
33	-0.006581	-0.0497	0.480274
34	0.091596	0.6915	0.246019
35	-0.111792	-0.844	0.201096
36	0.010187	0.0769	0.469481
37	0.042902	0.3239	0.373598
38	-0.063966	-0.4829	0.315498
39	0.062144	0.4692	0.320368
40	-0.019799	-0.1495	0.440852
41	-0.030284	-0.2286	0.409983
42	0.001467	0.0111	0.4956
43	0.047051	0.3552	0.361866
44	-0.029271	-0.221	0.412945
45	0.043463	0.3281	0.372005
46	0.003763	0.0284	0.488718
47	-0.002342	-0.0177	0.492976
48	0.034277	0.2588	0.398365
49	0.004721	0.0356	0.485846
50	-0.038479	-0.2905	0.38624
51	0.017192	0.1298	0.448591
52	0.018914	0.1428	0.443477
53	-0.011126	-0.084	0.466677
54	-0.007263	-0.0548	0.47823
55	-0.014467	-0.1092	0.456705
56	-0.017668	-0.1334	0.447176
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	-0.446026	-3.3674	0.000682
2	-0.206681	-1.5604	0.062099
3	0.360584	2.7224	0.004292
4	-0.044698	-0.3375	0.368503
5	-0.086543	-0.6534	0.258068
6	0.138927	1.0489	0.149331
7	-0.236257	-1.7837	0.039898
8	-0.115544	-0.8723	0.193342
9	-0.223782	-1.6895	0.048292
10	-0.075228	-0.568	0.286148
11	-0.079237	-0.5982	0.276029
12	-0.034632	-0.2615	0.397337
13	-0.000376	-0.0028	0.498872
14	-0.012715	-0.096	0.46193
15	0.132597	1.0011	0.160509
16	-0.196188	-1.4812	0.072032
17	-0.12088	-0.9126	0.182642
18	-0.059568	-0.4497	0.327306
19	-0.152825	-1.1538	0.126697
20	0.052775	0.3984	0.345897
21	0.000467	0.0035	0.498599
22	-0.212263	-1.6026	0.057281
23	0.107737	0.8134	0.209687
24	-0.072099	-0.5443	0.294166
25	-0.009204	-0.0695	0.472421
26	-0.089156	-0.6731	0.251798
27	0.109774	0.8288	0.205345
28	-0.09902	-0.7476	0.228893
29	-0.136436	-1.0301	0.153664
30	0.054732	0.4132	0.340499
31	-0.123077	-0.9292	0.178349
32	-0.039823	-0.3007	0.382386
33	-0.049024	-0.3701	0.356331
34	0.031543	0.2381	0.406313
35	-0.023228	-0.1754	0.430705
36	-0.069515	-0.5248	0.300868
37	-0.052625	-0.3973	0.346312
38	-0.109003	-0.823	0.206981
39	0.063691	0.4809	0.316229
40	-0.128941	-0.9735	0.167212
41	-0.097498	-0.7361	0.232347
42	-0.029482	-0.2226	0.412327
43	-0.058611	-0.4425	0.3299
44	-0.015241	-0.1151	0.454398
45	0.067341	0.5084	0.306562
46	-0.075832	-0.5725	0.284611
47	0.030033	0.2267	0.410716
48	0.003054	0.0231	0.490843
49	-0.021685	-0.1637	0.435267
50	-0.15991	-1.2073	0.116152
51	-0.035742	-0.2698	0.394127
52	0.027402	0.2069	0.418421
53	-0.039009	-0.2945	0.384717
54	0.063754	0.4813	0.31606
55	-0.001678	-0.0127	0.494967
56	0.00139	0.0105	0.495832
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/16/t1260994862lyz33msjxh1ry5i/10dqo1260994811.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260994862lyz33msjxh1ry5i/10dqo1260994811.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260994862lyz33msjxh1ry5i/2mtwh1260994811.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260994862lyz33msjxh1ry5i/2mtwh1260994811.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 0.0 ; 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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