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autocorrelatiefunctie met trend, consumptieprijzen

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Mon, 15 Nov 2010 11:14:14 +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/Nov/15/t12898195921qxmhv9q1gv9cks.htm/, Retrieved Mon, 15 Nov 2010 12:13:14 +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/Nov/15/t12898195921qxmhv9q1gv9cks.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:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

96.92 99.06 99.65 99.82 99.99 100.33 99.31 101.1 101.1 100.93 100.85 100.93 99.6 101.88 101.81 102.38 102.74 102.82 101.72 103.47 102.98 102.68 102.9 103.03 101.29 103.69 103.68 104.2 104.08 104.16 103.05 104.66 104.46 104.95 105.85 106.23 104.86 107.44 108.23 108.45 109.39 110.15 109.13 110.28 110.17 109.99 109.26 109.11 107.06 109.53 108.92 109.24 109.12 109 107.23 109.49 109.04 109.02 109.23 109.46

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	-0.436377	-3.3519	0.000703
2	0.094821	0.7283	0.234646
3	0.021964	0.1687	0.433302
4	0.070783	0.5437	0.29435
5	-0.454907	-3.4942	0.000454
6	0.740095	5.6848	0
7	-0.422538	-3.2456	0.000967
8	0.044994	0.3456	0.365433
9	-0.016767	-0.1288	0.448981
10	-0.00167	-0.0128	0.494905
11	-0.364592	-2.8005	0.003444
12	0.647744	4.9754	3e-06
13	-0.38532	-2.9597	0.002214
14	0.030493	0.2342	0.407811
15	0.032433	0.2491	0.402064
16	-0.012831	-0.0986	0.460912
17	-0.362743	-2.7863	0.00358
18	0.571945	4.3932	2.4e-05
19	-0.329762	-2.5329	0.006995
20	0.006802	0.0522	0.479254
21	-0.009698	-0.0745	0.470435
22	0.052664	0.4045	0.343647
23	-0.316564	-2.4316	0.009044
24	0.513344	3.9431	0.000108
25	-0.230853	-1.7732	0.040677
26	0.054956	0.4221	0.337235
27	-0.004994	-0.0384	0.484766
28	0.014903	0.1145	0.454627
29	-0.266777	-2.0492	0.022451
30	0.408022	3.1341	0.001343
31	-0.222607	-1.7099	0.046272
32	0.02691	0.2067	0.418478
33	0.033287	0.2557	0.399542
34	0.029708	0.2282	0.410143
35	-0.201409	-1.5471	0.063599
36	0.350582	2.6929	0.004604
37	-0.129961	-0.9982	0.161118
38	0.035259	0.2708	0.393734
39	0.002718	0.0209	0.491707
40	0.030758	0.2363	0.407027
41	-0.149298	-1.1468	0.128052
42	0.238303	1.8304	0.036118
43	-0.13769	-1.0576	0.147271
44	0.023129	0.1777	0.429802
45	-0.031071	-0.2387	0.406098
46	-0.027481	-0.2111	0.416773
47	-0.096737	-0.7431	0.230199
48	0.150285	1.1544	0.126503

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.436377	-3.3519	0.000703
2	-0.118092	-0.9071	0.184026
3	0.020913	0.1606	0.436463
4	0.126327	0.9703	0.167919
5	-0.472439	-3.6289	0.000298
6	0.577151	4.4332	2.1e-05
7	-0.077306	-0.5938	0.277458
8	-0.161353	-1.2394	0.110057
9	-0.137949	-1.0596	0.146821
10	-0.23053	-1.7707	0.040885
11	0.058245	0.4474	0.328118
12	0.202656	1.5566	0.062453
13	-0.044258	-0.34	0.367549
14	-0.154289	-1.1851	0.120362
15	-0.039702	-0.305	0.380735
16	0.021164	0.1626	0.435709
17	-0.154112	-1.1838	0.120629
18	-0.057381	-0.4407	0.330503
19	-0.018359	-0.141	0.444168
20	-0.046393	-0.3564	0.361424
21	-0.179405	-1.378	0.086699
22	0.059826	0.4595	0.323771
23	0.024625	0.1892	0.425312
24	-0.021513	-0.1652	0.434657
25	0.116057	0.8914	0.188155
26	0.037829	0.2906	0.3862
27	-0.025985	-0.1996	0.421242
28	-0.183525	-1.4097	0.081942
29	-0.009738	-0.0748	0.470312
30	-0.091734	-0.7046	0.241908
31	-0.095406	-0.7328	0.233282
32	0.028829	0.2214	0.412758
33	0.08131	0.6246	0.267335
34	0.094759	0.7279	0.234789
35	0.114412	0.8788	0.191534
36	0.00747	0.0574	0.47722
37	-0.005917	-0.0454	0.481951
38	0.056727	0.4357	0.332311
39	-0.025913	-0.199	0.421457
40	-0.042065	-0.3231	0.373878
41	0.072464	0.5566	0.289952
42	0.033486	0.2572	0.398955
43	0.009663	0.0742	0.470543
44	-0.030122	-0.2314	0.408913
45	0.018763	0.1441	0.442947
46	-0.071131	-0.5464	0.293438
47	0.021248	0.1632	0.435455
48	-0.110609	-0.8496	0.199491

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/15/t12898195921qxmhv9q1gv9cks/1gxkh1289819652.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t12898195921qxmhv9q1gv9cks/1gxkh1289819652.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t12898195921qxmhv9q1gv9cks/2r6j21289819652.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t12898195921qxmhv9q1gv9cks/2r6j21289819652.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 (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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