Home » date » 2010 » Dec » 28 »

ACF met d=1=D Werkloosheid 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 10:54:16 +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/t1293533568rz2l8kzjpmuwhg9.htm/, Retrieved Tue, 28 Dec 2010 11:52:48 +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/t1293533568rz2l8kzjpmuwhg9.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	0.193031	2.006	0.023676
2	0.146394	1.5214	0.065544
3	0.127492	1.3249	0.093995
4	0.152872	1.5887	0.057526
5	0.132203	1.3739	0.08616
6	0.127833	1.3285	0.09341
7	0.058163	0.6044	0.273407
8	0.12645	1.3141	0.095797
9	0.101046	1.0501	0.148008
10	-0.100005	-1.0393	0.150497
11	0.06195	0.6438	0.260534
12	-0.232062	-2.4117	0.008783
13	-0.057307	-0.5956	0.27636
14	0.106375	1.1055	0.135703
15	-0.015325	-0.1593	0.436881
16	-0.085714	-0.8908	0.187518
17	-0.071547	-0.7435	0.229385
18	-0.052459	-0.5452	0.293381
19	-0.01988	-0.2066	0.418355
20	-0.090643	-0.942	0.17415
21	-0.152135	-1.581	0.058398
22	-0.039758	-0.4132	0.340149
23	-0.013307	-0.1383	0.445134
24	-0.20878	-2.1697	0.016111
25	-0.14252	-1.4811	0.070744
26	-0.265534	-2.7595	0.003401
27	-0.117545	-1.2216	0.112265
28	-0.121915	-1.267	0.103944
29	-0.042653	-0.4433	0.329232
30	-0.13001	-1.3511	0.089744
31	-0.056172	-0.5838	0.280299
32	-0.048349	-0.5025	0.308185
33	-0.024679	-0.2565	0.399038
34	-0.025453	-0.2645	0.395945
35	-0.004733	-0.0492	0.48043
36	0.02507	0.2605	0.397472
37	0.027559	0.2864	0.38756
38	0.096231	1.0001	0.159758
39	-0.081051	-0.8423	0.20074
40	-0.005781	-0.0601	0.476103
41	-0.000483	-0.005	0.498002
42	0.020253	0.2105	0.416846
43	0.013318	0.1384	0.44509
44	-0.038087	-0.3958	0.346511
45	-0.086966	-0.9038	0.184061
46	-0.021098	-0.2193	0.413432
47	-0.105527	-1.0967	0.137613
48	-0.04381	-0.4553	0.32491

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.193031	2.006	0.023676
2	0.113357	1.178	0.120685
3	0.084762	0.8809	0.190171
4	0.107514	1.1173	0.133168
5	0.071876	0.747	0.228358
6	0.064844	0.6739	0.250914
7	-0.012932	-0.1344	0.44667
8	0.077063	0.8009	0.212486
9	0.035601	0.37	0.356061
10	-0.182486	-1.8965	0.030286
11	0.063419	0.6591	0.255628
12	-0.297744	-3.0942	0.001256
13	0.00218	0.0227	0.490982
14	0.181167	1.8827	0.031213
15	-0.035311	-0.367	0.357182
16	-0.032905	-0.342	0.366525
17	-0.044867	-0.4663	0.320979
18	0.023876	0.2481	0.402255
19	0.013173	0.1369	0.445682
20	-0.081506	-0.847	0.199424
21	-0.041089	-0.427	0.335112
22	-0.10024	-1.0417	0.149934
23	0.070295	0.7305	0.233325
24	-0.234159	-2.4335	0.008298
25	-0.090215	-0.9375	0.175286
26	-0.122324	-1.2712	0.103189
27	-0.00459	-0.0477	0.481023
28	-0.04571	-0.475	0.317861
29	0.078792	0.8188	0.207344
30	-0.020595	-0.214	0.415464
31	0.055365	0.5754	0.283118
32	0.039731	0.4129	0.340251
33	0.022665	0.2355	0.407118
34	-0.030755	-0.3196	0.374938
35	0.136903	1.4227	0.078848
36	-0.140964	-1.4649	0.072921
37	-0.035698	-0.371	0.355686
38	0.01783	0.1853	0.426673
39	-0.140485	-1.46	0.073601
40	-0.040114	-0.4169	0.338799
41	0.010569	0.1098	0.456373
42	-0.056442	-0.5866	0.279361
43	0.02423	0.2518	0.400835
44	-0.045176	-0.4695	0.319836
45	-0.079125	-0.8223	0.20636
46	-0.091459	-0.9505	0.171999
47	-0.041351	-0.4297	0.334124
48	-0.040073	-0.4165	0.338953

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/1o85n1293533652.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/1o85n1293533652.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/2yhn81293533652.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/2yhn81293533652.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/3yhn81293533652.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/28/t1293533568rz2l8kzjpmuwhg9/3yhn81293533652.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; 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 (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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