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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 08:49:55 -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/t12607195563cgsnz39sv935q2.htm/, Retrieved Sun, 13 Dec 2009 16:52:39 +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/t12607195563cgsnz39sv935q2.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	10 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.47815	4.6111	6e-06
2	0.56707	5.4686	0
3	0.651571	6.2835	0
4	0.361811	3.4892	0.000371
5	0.436861	4.2129	2.9e-05
6	0.35306	3.4048	0.000489
7	0.14987	1.4453	0.075869
8	0.204769	1.9747	0.025633
9	0.092376	0.8908	0.187655
10	0.016558	0.1597	0.43674
11	0.061917	0.5971	0.275945
12	-0.076947	-0.7421	0.229963
13	-0.025339	-0.2444	0.403744
14	-0.001136	-0.011	0.495642
15	-0.023591	-0.2275	0.410266
16	-0.080718	-0.7784	0.219151
17	0.013337	0.1286	0.44897
18	-0.025236	-0.2434	0.404128
19	-0.117489	-1.133	0.130059
20	0.009558	0.0922	0.463378
21	-0.033382	-0.3219	0.374117
22	-0.148727	-1.4343	0.077425
23	0.065106	0.6279	0.265817
24	-0.167716	-1.6174	0.05459
25	-0.125614	-1.2114	0.11441
26	-0.009594	-0.0925	0.463242
27	-0.18144	-1.7497	0.041731
28	-0.113434	-1.0939	0.138408
29	-0.102241	-0.986	0.16335
30	-0.226376	-2.1831	0.015773
31	-0.121069	-1.1675	0.122987
32	-0.140998	-1.3597	0.088601
33	-0.22446	-2.1646	0.016489
34	-0.135841	-1.31	0.096711
35	-0.209799	-2.0232	0.02296
36	-0.143728	-1.3861	0.084521
37	-0.097944	-0.9445	0.17367
38	-0.108659	-1.0479	0.148707
39	-0.111289	-1.0732	0.142973
40	-0.019913	-0.192	0.424069
41	-0.015867	-0.153	0.43936
42	-0.030214	-0.2914	0.385708
43	0.055562	0.5358	0.296681
44	0.070755	0.6823	0.24836
45	0.01442	0.1391	0.444852
46	0.11878	1.1455	0.127477
47	0.05432	0.5238	0.300818
48	-0.022482	-0.2168	0.414416
49	0.095524	0.9212	0.179666
50	-0.043679	-0.4212	0.337281
51	-0.042921	-0.4139	0.339945
52	-0.002262	-0.0218	0.491321
53	-0.118688	-1.1446	0.12766
54	-0.032839	-0.3167	0.376094
55	-0.078841	-0.7603	0.224496
56	-0.175212	-1.6897	0.04722
57	-0.063788	-0.6152	0.269978
58	-0.109382	-1.0548	0.147115
59	-0.123209	-1.1882	0.118892
60	-0.040013	-0.3859	0.350238

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.47815	4.6111	6e-06
2	0.438754	4.2312	2.7e-05
3	0.46494	4.4837	1e-05
4	-0.164858	-1.5898	0.057633
5	-0.091193	-0.8794	0.190718
6	-0.109949	-1.0603	0.145874
7	-0.216423	-2.0871	0.019807
8	-0.083807	-0.8082	0.210516
9	-0.006079	-0.0586	0.476689
10	0.06134	0.5915	0.277796
11	0.106808	1.03	0.152837
12	-0.04712	-0.4544	0.325298
13	0.051074	0.4925	0.31175
14	0.077855	0.7508	0.227332
15	0.146058	1.4085	0.081153
16	-0.214364	-2.0673	0.020744
17	-0.026612	-0.2566	0.399014
18	-0.006862	-0.0662	0.47369
19	-0.21647	-2.0876	0.019786
20	-0.024017	-0.2316	0.408672
21	0.165326	1.5943	0.057126
22	-0.062847	-0.6061	0.27297
23	0.207433	2.0004	0.024186
24	-0.205662	-1.9833	0.02514
25	-0.076439	-0.7372	0.231442
26	0.009589	0.0925	0.463262
27	0.081183	0.7829	0.217836
28	-0.151701	-1.463	0.073425
29	-0.049748	-0.4797	0.316266
30	-0.064284	-0.6199	0.26841
31	-0.062523	-0.603	0.274003
32	0.043765	0.422	0.336981
33	0.117379	1.132	0.13028
34	-0.062044	-0.5983	0.275538
35	-0.03145	-0.3033	0.381171
36	0.060007	0.5787	0.282099
37	0.091631	0.8837	0.189579
38	0.052557	0.5068	0.306734
39	0.003334	0.0321	0.487212
40	-0.071989	-0.6942	0.244633
41	-0.017992	-0.1735	0.431313
42	-0.03394	-0.3273	0.372087
43	-0.048448	-0.4672	0.320718
44	0.094818	0.9144	0.181439
45	0.113481	1.0944	0.13831
46	-0.092939	-0.8963	0.186212
47	-0.075133	-0.7246	0.235271
48	-0.174899	-1.6867	0.04751
49	0.013329	0.1285	0.449
50	-0.020285	-0.1956	0.422668
51	0.038464	0.3709	0.355764
52	-0.020511	-0.1978	0.421814
53	-0.001963	-0.0189	0.492467
54	0.071471	0.6892	0.246195
55	-0.065127	-0.6281	0.265751
56	-0.05438	-0.5244	0.300616
57	0.000997	0.0096	0.496174
58	-0.032788	-0.3162	0.37628
59	-0.067842	-0.6542	0.257283
60	0.028132	0.2713	0.393383

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/13/t12607195563cgsnz39sv935q2/15zu11260719384.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t12607195563cgsnz39sv935q2/15zu11260719384.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t12607195563cgsnz39sv935q2/2kbcy1260719384.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t12607195563cgsnz39sv935q2/2kbcy1260719384.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; 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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