Home » date » 2010 » Dec » 28 »

ACF met d=1 Werloosheid Belgie 2000 - 2010

*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: Tue, 28 Dec 2010 10:49:28 +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/28/t1293533274e9npov6nb6oxccu.htm/, Retrieved Tue, 28 Dec 2010 11:47:54 +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/28/t1293533274e9npov6nb6oxccu.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:

Data Paper Statistiek

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

464 460 467 460 448 443 436 431 484 510 513 503 471 471 476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516 528 533 536 537 524 536 587 597 581 564 558 575 580 575 563 552 537 545 601 604 586 564 549

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.268623	2.9426	0.001954
2	-0.228985	-2.5084	0.006731
3	-0.3379	-3.7015	0.000163
4	-0.276495	-3.0289	0.001503
5	0.083162	0.911	0.182062
6	0.235772	2.5828	0.005501
7	0.086286	0.9452	0.173225
8	-0.240416	-2.6336	0.00478
9	-0.294043	-3.2211	0.000822
10	-0.205996	-2.2566	0.012922
11	0.263305	2.8844	0.002325
12	0.805818	8.8273	0
13	0.169321	1.8548	0.033038
14	-0.225011	-2.4649	0.007561
15	-0.30135	-3.3011	0.000634
16	-0.232134	-2.5429	0.006133
17	0.07334	0.8034	0.211666
18	0.184209	2.0179	0.022915
19	0.035651	0.3905	0.348417
20	-0.252826	-2.7696	0.003253
21	-0.278713	-3.0531	0.001395
22	-0.169554	-1.8574	0.032855
23	0.247027	2.706	0.003901
24	0.693506	7.597	0
25	0.125231	1.3718	0.086337
26	-0.22929	-2.5117	0.006671
27	-0.294745	-3.2288	0.000802
28	-0.220857	-2.4194	0.008524
29	0.068546	0.7509	0.227095
30	0.146749	1.6075	0.055281
31	0.025274	0.2769	0.39118
32	-0.233428	-2.5571	0.005901
33	-0.240243	-2.6317	0.004806
34	-0.122567	-1.3427	0.090959
35	0.22726	2.4895	0.007081
36	0.601092	6.5846	0
37	0.104075	1.1401	0.128262
38	-0.187292	-2.0517	0.021188
39	-0.257782	-2.8239	0.002779
40	-0.17249	-1.8895	0.030617
41	0.055679	0.6099	0.271531
42	0.126883	1.3899	0.083561
43	0.016291	0.1785	0.42933
44	-0.215602	-2.3618	0.009898
45	-0.192901	-2.1131	0.018331
46	-0.074577	-0.817	0.207786
47	0.195614	2.1428	0.017072
48	0.508967	5.5755	0

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.268623	2.9426	0.001954
2	-0.324563	-3.5554	0.00027
3	-0.203879	-2.2334	0.013688
4	-0.228218	-2.5	0.006885
5	0.100168	1.0973	0.137358
6	0.014819	0.1623	0.435659
7	-0.062542	-0.6851	0.247298
8	-0.277023	-3.0346	0.001477
9	-0.126711	-1.388	0.083847
10	-0.255523	-2.7991	0.002986
11	0.229818	2.5175	0.006568
12	0.681493	7.4654	0
13	-0.257618	-2.8221	0.002793
14	0.099081	1.0854	0.139965
15	0.110347	1.2088	0.114561
16	0.059397	0.6507	0.258254
17	-0.100875	-1.105	0.135679
18	-0.083663	-0.9165	0.180626
19	-0.074463	-0.8157	0.208145
20	-0.127977	-1.4019	0.08176
21	-0.101855	-1.1158	0.133376
22	-0.038127	-0.4177	0.33847
23	-0.123887	-1.3571	0.088647
24	0.121511	1.3311	0.092842
25	-0.015279	-0.1674	0.43368
26	-0.061626	-0.6751	0.250461
27	-0.045623	-0.4998	0.309073
28	-0.017949	-0.1966	0.422228
29	-0.0035	-0.0383	0.48474
30	-0.107336	-1.1758	0.121001
31	0.020173	0.221	0.41274
32	-0.02847	-0.3119	0.377838
33	-0.005872	-0.0643	0.47441
34	0.02653	0.2906	0.385922
35	-0.054778	-0.6001	0.274796
36	0.029651	0.3248	0.372944
37	0.038461	0.4213	0.337139
38	0.081768	0.8957	0.186097
39	-0.024567	-0.2691	0.394149
40	0.06639	0.7273	0.234238
41	-0.045173	-0.4948	0.310807
42	0.064985	0.7119	0.238961
43	-0.057707	-0.6321	0.264247
44	-0.008506	-0.0932	0.46296
45	-0.024955	-0.2734	0.392519
46	0.013036	0.1428	0.443342
47	-0.130647	-1.4312	0.077491
48	-0.027522	-0.3015	0.381781

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/111np1293533364.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/111np1293533364.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/2utms1293533364.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/2utms1293533364.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/3m24d1293533364.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533274e9npov6nb6oxccu/3m24d1293533364.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 (par8 != '') par8 <- as.numeric(par8)

ox <- x

if (par8 == '') {

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

} else {

x <- log(x,base=par8)

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='picts.png')

op <- par(mfrow=c(2,1))

plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')

if (par8=='') {

mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

} else {

mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

}

plot(x,type='l', main=mytitle,xlab='time',ylab='value')

par(op)

dev.off()

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)

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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