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(P)ACF inschrijvingen nieuwe personenwagens

*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, 21 Dec 2008 04:27:19 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/21/t1229858957t7x6ot6s3sixrtu.htm/, Retrieved Sun, 21 Dec 2008 12:29:19 +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/2008/Dec/21/t1229858957t7x6ot6s3sixrtu.htm/},
    year = {2008},
}
@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 = {2008},
    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 «

11.514 31.514 27.071 29.462 26.105 22.397 23.843 21.705 18.089 20.764 25.316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698 31956 29506 34506 27165 26736 23691 18157 17328 18205 20995 17382 9367 31124 26551 30651 25859 25100 25778 20418 18688 20424 24776 19814 12738

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.775796	6.0592	0
2	0.675321	5.2744	1e-06
3	0.518627	4.0506	7.3e-05
4	0.394049	3.0776	0.001562
5	0.267387	2.0884	0.020473
6	0.10726	0.8377	0.202726
7	0.108837	0.85	0.199312
8	0.046332	0.3619	0.359352
9	0.018878	0.1474	0.441634
10	0.008907	0.0696	0.472384
11	-0.015405	-0.1203	0.452313
12	0.106434	0.8313	0.204529
13	-0.023561	-0.184	0.427304
14	-0.00871	-0.068	0.472993
15	-0.058695	-0.4584	0.324139
16	-0.046072	-0.3598	0.360107
17	-0.06204	-0.4845	0.314866
18	-0.131285	-1.0254	0.154619
19	-0.078495	-0.6131	0.271055
20	-0.117245	-0.9157	0.181711
21	-0.094356	-0.7369	0.23199
22	-0.061155	-0.4776	0.317309
23	-0.019885	-0.1553	0.438546
24	0.068965	0.5386	0.29605
25	-0.020563	-0.1606	0.436468
26	0.008029	0.0627	0.4751
27	-0.048018	-0.375	0.354469
28	-0.060662	-0.4738	0.318673
29	-0.107402	-0.8388	0.202419
30	-0.149441	-1.1672	0.123842
31	-0.125367	-0.9791	0.165687
32	-0.155518	-1.2146	0.114594
33	-0.138627	-1.0827	0.141599
34	-0.115387	-0.9012	0.185513
35	-0.093045	-0.7267	0.235094
36	-0.051462	-0.4019	0.344569
37	-0.105813	-0.8264	0.205893
38	-0.055745	-0.4354	0.33241
39	-0.07616	-0.5948	0.277079
40	-0.061613	-0.4812	0.316043
41	-0.081468	-0.6363	0.263485
42	-0.085828	-0.6703	0.252587
43	-0.084479	-0.6598	0.255931
44	-0.119465	-0.9331	0.177236
45	-0.137898	-1.077	0.142857
46	-0.144137	-1.1257	0.132342
47	-0.141103	-1.1021	0.137384
48	-0.149552	-1.168	0.123668
49	-0.181412	-1.4169	0.080803
50	-0.129517	-1.0116	0.157873
51	-0.106976	-0.8355	0.203345
52	-0.072647	-0.5674	0.286266
53	-0.052092	-0.4069	0.34277
54	-0.033718	-0.2633	0.396585
55	-0.013378	-0.1045	0.458563
56	-0.008444	-0.0659	0.473817
57	-0.008482	-0.0662	0.473699
58	-0.003543	-0.0277	0.489008
59	0.013911	0.1086	0.456918
60	0.017132	0.1338	0.446999

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.775796	6.0592	0
2	0.18451	1.4411	0.077339
3	-0.134587	-1.0512	0.148667
4	-0.065236	-0.5095	0.306118
5	-0.065626	-0.5126	0.305055
6	-0.191972	-1.4993	0.069471
7	0.262639	2.0513	0.022271
8	-0.018928	-0.1478	0.441481
9	-0.080726	-0.6305	0.265364
10	0.061528	0.4805	0.316279
11	-0.07358	-0.5747	0.283812
12	0.315824	2.4667	0.008231
13	-0.441362	-3.4471	0.000516
14	0.076989	0.6013	0.274934
15	0.002532	0.0198	0.492144
16	0.051904	0.4054	0.343307
17	0.002225	0.0174	0.493095
18	-0.077549	-0.6057	0.273488
19	-0.00854	-0.0667	0.473519
20	-0.039481	-0.3084	0.37943
21	0.075786	0.5919	0.27805
22	0.138073	1.0784	0.142554
23	0.075993	0.5935	0.277512
24	-0.223005	-1.7417	0.043299
25	-0.074873	-0.5848	0.280428
26	-0.014984	-0.117	0.453612
27	0.03057	0.2388	0.406046
28	-0.05094	-0.3979	0.346064
29	-0.067274	-0.5254	0.300596
30	0.092616	0.7234	0.236112
31	-0.137098	-1.0708	0.144245
32	0.151292	1.1816	0.120969
33	-0.062617	-0.4891	0.31328
34	0.033943	0.2651	0.395911
35	-0.161199	-1.259	0.106413
36	-0.003279	-0.0256	0.489827
37	0.082135	0.6415	0.261803
38	0.03362	0.2626	0.396879
39	-0.057531	-0.4493	0.327393
40	-0.095797	-0.7482	0.228609
41	0.06217	0.4856	0.314508
42	-0.064344	-0.5025	0.308548
43	0.041153	0.3214	0.374496
44	-0.076013	-0.5937	0.27746
45	-0.088259	-0.6893	0.246617
46	-0.116066	-0.9065	0.184118
47	0.078514	0.6132	0.271006
48	-0.032054	-0.2503	0.40158
49	0.027559	0.2152	0.415149
50	0.016106	0.1258	0.450156
51	0.006551	0.0512	0.479681
52	0.072291	0.5646	0.287204
53	-0.020265	-0.1583	0.437383
54	-0.099058	-0.7737	0.221059
55	0.013883	0.1084	0.457005
56	0.014678	0.1146	0.454555
57	-0.043968	-0.3434	0.366239
58	0.016954	0.1324	0.447545
59	0.033896	0.2647	0.396054
60	0.011002	0.0859	0.465902

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229858957t7x6ot6s3sixrtu/1phql1229858837.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229858957t7x6ot6s3sixrtu/1phql1229858837.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229858957t7x6ot6s3sixrtu/2nep11229858837.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229858957t7x6ot6s3sixrtu/2nep11229858837.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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