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Paper statistiek: stationair maken tijdreeks bakmeel

*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, 29 Nov 2009 07:02:09 -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/Nov/29/t1259503401ub3jk7zjwrue08q.htm/, Retrieved Sun, 29 Nov 2009 15:03:23 +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/Nov/29/t1259503401ub3jk7zjwrue08q.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:

ETSHWP(13)

Dataseries X:

» Textbox « » Textfile « » CSV «

0.51 0.51 0.51 0.51 0.52 0.52 0.52 0.53 0.53 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.53 0.53 0.53 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.53 0.53 0.53 0.53 0.53 0.54 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.56 0.56 0.56 0.56 0.56 0.55 0.56 0.55 0.55 0.56 0.55 0.55 0.55 0.55

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.165767	-1.2733	0.103956
2	-0.093262	-0.7164	0.238297
3	0.270601	2.0785	0.02101
4	-0.166771	-1.281	0.102604
5	-0.162168	-1.2456	0.108911
6	-0.016824	-0.1292	0.44881
7	-0.089998	-0.6913	0.246048
8	0.060285	0.4631	0.322514
9	0.122913	0.9441	0.174482
10	-0.24162	-1.8559	0.034231
11	-0.023436	-0.18	0.428879
12	0.049069	0.3769	0.353798
13	-0.242624	-1.8636	0.033676
14	-0.092341	-0.7093	0.24047
15	0.198682	1.5261	0.066164
16	-0.020172	-0.1549	0.438698
17	0.052333	0.402	0.344576
18	0.124838	0.9589	0.170762
19	0.056602	0.4348	0.332659
20	-0.089412	-0.6868	0.247454
21	0.055932	0.4296	0.334517
22	-0.007366	-0.0566	0.477537
23	-0.002762	-0.0212	0.491572
24	0.142582	1.0952	0.138941
25	-0.076271	-0.5859	0.280105
26	-0.003766	-0.0289	0.488509
27	0.068738	0.528	0.299744
28	-0.155053	-1.191	0.119214
29	-0.155388	-1.1936	0.118714
30	0.135635	1.0418	0.15087
31	-0.010379	-0.0797	0.468365
32	-0.088491	-0.6797	0.249672
33	0.202532	1.5557	0.062567
34	-0.089161	-0.6849	0.248058
35	-0.016656	-0.1279	0.449316
36	0.055849	0.429	0.33475
37	-0.158067	-1.2141	0.114767
38	-0.002846	-0.0219	0.491317
39	0.069659	0.5351	0.29731
40	-0.003515	-0.027	0.489275
41	0.001088	0.0084	0.49668
42	0.146432	1.1248	0.132621
43	-0.072421	-0.5563	0.290063
44	8.4e-05	6e-04	0.499745
45	0.072588	0.5576	0.289626
46	-0.141327	-1.0856	0.141047
47	0.004018	0.0309	0.487743
48	0.149362	1.1473	0.127951

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.165767	-1.2733	0.103956
2	-0.124152	-0.9536	0.17208
3	0.242959	1.8662	0.033493
4	-0.101652	-0.7808	0.219019
5	-0.175232	-1.346	0.091729
6	-0.169956	-1.3055	0.098403
7	-0.087834	-0.6747	0.251262
8	0.102313	0.7859	0.21754
9	0.165292	1.2696	0.1046
10	-0.255521	-1.9627	0.027201
11	-0.253743	-1.949	0.028025
12	-0.127379	-0.9784	0.165932
13	-0.101826	-0.7821	0.21863
14	-0.129026	-0.9911	0.162851
15	0.071437	0.5487	0.292635
16	-0.015338	-0.1178	0.453309
17	-0.032984	-0.2534	0.400436
18	-0.059479	-0.4569	0.324723
19	0.091603	0.7036	0.24222
20	-0.133179	-1.023	0.155249
21	0.02403	0.1846	0.427097
22	0.045506	0.3495	0.363965
23	0.043012	0.3304	0.371142
24	0.05312	0.408	0.342368
25	-0.038679	-0.2971	0.383719
26	-0.07926	-0.6088	0.272495
27	-0.010664	-0.0819	0.467497
28	-0.006077	-0.0467	0.481464
29	-0.060546	-0.4651	0.321799
30	0.057934	0.445	0.328975
31	0.119297	0.9163	0.181611
32	-0.019193	-0.1474	0.441649
33	0.085807	0.6591	0.2562
34	-0.128733	-0.9888	0.163395
35	0.020455	0.1571	0.437844
36	0.019086	0.1466	0.441971
37	0.02255	0.1732	0.431538
38	-0.074382	-0.5713	0.284969
39	-0.111882	-0.8594	0.196803
40	0.02801	0.2151	0.415197
41	-0.008595	-0.066	0.473793
42	0.066587	0.5115	0.305468
43	-0.029138	-0.2238	0.411838
44	0.042953	0.3299	0.371313
45	0.049078	0.377	0.353774
46	-0.041804	-0.3211	0.374634
47	-0.036382	-0.2795	0.390437
48	0.05979	0.4593	0.323868

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503401ub3jk7zjwrue08q/18f421259503327.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503401ub3jk7zjwrue08q/18f421259503327.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503401ub3jk7zjwrue08q/228lf1259503327.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/29/t1259503401ub3jk7zjwrue08q/228lf1259503327.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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