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Bruto Industriële Productie

*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: Sun, 13 Dec 2009 08:58:37 -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/13/t1260719956mefy82jnqzu32o2.htm/, Retrieved Sun, 13 Dec 2009 16:59:18 +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/13/t1260719956mefy82jnqzu32o2.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 «

98.8 100.5 110.4 96.4 101.9 106.2 81 94.7 101 109.4 102.3 90.7 96.2 96.1 106 103.1 102 104.7 86 92.1 106.9 112.6 101.7 92 97.4 97 105.4 102.7 98.1 104.5 87.4 89.9 109.8 111.7 98.6 96.9 95.1 97 112.7 102.9 97.4 111.4 87.4 96.8 114.1 110.3 103.9 101.6 94.6 95.9 104.7 102.8 98.1 113.9 80.9 95.7 113.2 105.9 108.8 102.3 99 100.7 115.5 100.7 109.9 114.6 85.4 100.5 114.8 116.5 112.9 102 106 105.3 118.8 106.1 109.3 117.2 92.5 104.2 112.5 122.4 113.3 100 110.7 112.8 109.8 117.3 109.1 115.9 96 99.8 116.8 115.7 99.4 94.3 91 93.2 103.1 94.1 91.8 102.7 82.6 89.1 104.5

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	-0.60241	-5.7781	0
2	-0.003473	-0.0333	0.48675
3	0.377203	3.618	0.000242
4	-0.377393	-3.6198	0.000241
5	0.139488	1.3379	0.09211
6	0.168187	1.6132	0.055064
7	-0.296928	-2.848	0.002713
8	0.169527	1.626	0.053681
9	0.001583	0.0152	0.493959
10	-0.14574	-1.3979	0.082754
11	0.20385	1.9553	0.026794
12	-0.157861	-1.5141	0.066708
13	0.002281	0.0219	0.491296
14	0.06786	0.6509	0.258371
15	0.020877	0.2002	0.420867
16	-0.148663	-1.4259	0.078637
17	0.165965	1.5919	0.057421
18	-0.003268	-0.0313	0.487529
19	-0.172639	-1.6559	0.050575
20	0.16341	1.5674	0.06023
21	0.050782	0.4871	0.313678
22	-0.32087	-3.0777	0.001374
23	0.462795	4.439	1.3e-05
24	-0.299757	-2.8752	0.002508
25	-0.055116	-0.5287	0.299159
26	0.298952	2.8674	0.002565
27	-0.254413	-2.4402	0.008297
28	0.046761	0.4485	0.327416
29	0.155117	1.4878	0.070108
30	-0.237187	-2.275	0.012614
31	0.131432	1.2607	0.105311
32	0.068394	0.656	0.256726
33	-0.194405	-1.8647	0.032708
34	0.177141	1.6991	0.046342
35	-0.120796	-1.1586	0.124802
36	-0.008116	-0.0778	0.469059
37	0.064809	0.6216	0.267863
38	-0.012336	-0.1183	0.453034
39	-0.099844	-0.9577	0.170369
40	0.118573	1.1373	0.12918
41	-0.020282	-0.1945	0.423092
42	-0.067351	-0.646	0.259941
43	0.055975	0.5369	0.296319
44	0.069942	0.6709	0.251997
45	-0.1717	-1.6469	0.051496
46	0.184152	1.7663	0.040329
47	-0.016519	-0.1584	0.437228
48	-0.181623	-1.7421	0.042419
49	0.254492	2.441	0.00828
50	-0.151439	-1.4526	0.074875
51	-0.021055	-0.2019	0.420202
52	0.157725	1.5128	0.066873
53	-0.208971	-2.0044	0.023985
54	0.110038	1.0554	0.146993
55	0.06932	0.6649	0.253892
56	-0.206318	-1.9789	0.025407
57	0.174934	1.6779	0.048379
58	-0.033403	-0.3204	0.374699
59	-0.117691	-1.1289	0.130947
60	0.162673	1.5603	0.061061

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.60241	-5.7781	0
2	-0.575058	-5.5158	0
3	0.064462	0.6183	0.268953
4	0.008419	0.0808	0.467908
5	-0.017135	-0.1644	0.434905
6	0.163294	1.5663	0.060361
7	0.041184	0.395	0.346869
8	-0.0668	-0.6407	0.261646
9	-0.139047	-1.3337	0.092799
10	-0.147293	-1.4128	0.080546
11	0.041331	0.3964	0.346353
12	-0.028561	-0.2739	0.392369
13	-0.047769	-0.4582	0.32395
14	-0.138969	-1.3329	0.092922
15	0.1645	1.5778	0.059018
16	-0.061225	-0.5872	0.279237
17	-0.047384	-0.4545	0.325274
18	0.169369	1.6245	0.053842
19	0.029522	0.2832	0.388844
20	-0.16386	-1.5717	0.059728
21	0.088729	0.8511	0.198473
22	-0.223721	-2.1459	0.017259
23	0.221671	2.1262	0.018082
24	0.05154	0.4944	0.311116
25	-0.001243	-0.0119	0.495256
26	-0.072579	-0.6961	0.244045
27	0.152745	1.4651	0.073154
28	-0.021334	-0.2046	0.419158
29	-0.029815	-0.286	0.387771
30	-0.00077	-0.0074	0.497063
31	0.01527	0.1465	0.441937
32	-0.069877	-0.6702	0.252191
33	0.063308	0.6072	0.272599
34	-0.067557	-0.648	0.259305
35	-0.070721	-0.6783	0.249633
36	-0.124157	-1.1909	0.118385
37	-0.099343	-0.9529	0.171578
38	-0.078643	-0.7543	0.226292
39	0.039894	0.3826	0.351431
40	-0.042813	-0.4107	0.341141
41	0.038023	0.3647	0.358084
42	0.086384	0.8286	0.204747
43	-0.031687	-0.3039	0.380935
44	-0.068852	-0.6604	0.255323
45	0.091756	0.8801	0.190551
46	-0.009934	-0.0953	0.462148
47	0.152107	1.459	0.073991
48	-0.044184	-0.4238	0.336352
49	0.017289	0.1658	0.434326
50	-0.07557	-0.7248	0.235194
51	0.109482	1.0501	0.148208
52	0.020502	0.1967	0.422267
53	-0.03911	-0.3751	0.354215
54	0.030233	0.29	0.386239
55	0.004387	0.0421	0.483263
56	-0.102833	-0.9863	0.163277
57	-0.00364	-0.0349	0.486111
58	0.035088	0.3366	0.36861
59	0.006156	0.059	0.476521
60	0.000724	0.0069	0.497238

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260719956mefy82jnqzu32o2/118341260719916.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260719956mefy82jnqzu32o2/118341260719916.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260719956mefy82jnqzu32o2/2s8pj1260719916.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260719956mefy82jnqzu32o2/2s8pj1260719916.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; 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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