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Opgave 6 bis oefening 2 stap 1

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 18 Nov 2010 17:56:27 +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/18/t1290102928e2cd183oc5ezwix.htm/, Retrieved Thu, 18 Nov 2010 18:55:30 +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/18/t1290102928e2cd183oc5ezwix.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 «

105,23 105,22 105,13 105 105,01 105,01 105,01 105,01 105,57 106,05 106,09 106,2 106,19 106,2 106,09 106,23 106,23 106,22 106,22 106,61 106,95 107,74 107,8 107,8 107,2 107,56 107,72 108,14 108,16 108,16 108,16 108,1 108,95 110,49 110,72 110,82 110,82 110,75 110,71 110,86 110,84 110,84 110,84 110,92 111,46 112,46 113,04 113,15 113,15 113,21 113,37 113,47 113,71 113,71 113,71 113,8 115,46 117 117,94 118,08 118,08 118,47 118,49 118,45 118,54 118,55 118,55 118,55 119,04 121,37 122 122,14

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.950207	8.0628	0
2	0.895307	7.5969	0
3	0.841911	7.1439	0
4	0.802464	6.8091	0
5	0.765386	6.4945	0
6	0.727202	6.1705	0
7	0.687539	5.834	0
8	0.64678	5.4881	0
9	0.607466	5.1545	1e-06
10	0.569519	4.8325	4e-06
11	0.530288	4.4996	1.3e-05
12	0.489307	4.1519	4.5e-05
13	0.441327	3.7448	0.00018
14	0.388503	3.2966	0.000761
15	0.339081	2.8772	0.002638
16	0.299484	2.5412	0.006601
17	0.270006	2.2911	0.012444
18	0.23996	2.0361	0.022709
19	0.208843	1.7721	0.040305
20	0.178108	1.5113	0.067545
21	0.149652	1.2698	0.104115
22	0.124416	1.0557	0.147317
23	0.099668	0.8457	0.200257
24	0.071952	0.6105	0.271715
25	0.037039	0.3143	0.377106
26	0.000167	0.0014	0.499435
27	-0.033926	-0.2879	0.387137
28	-0.060719	-0.5152	0.303989
29	-0.084412	-0.7163	0.238073
30	-0.108282	-0.9188	0.180634
31	-0.132863	-1.1274	0.131663
32	-0.158441	-1.3444	0.091518
33	-0.181201	-1.5375	0.064273
34	-0.197737	-1.6779	0.048856
35	-0.21396	-1.8155	0.036805
36	-0.232105	-1.9695	0.026373
37	-0.25418	-2.1568	0.017181
38	-0.278983	-2.3672	0.010306
39	-0.303599	-2.5761	0.006022
40	-0.318434	-2.702	0.004295
41	-0.328205	-2.7849	0.003419
42	-0.338736	-2.8743	0.00266
43	-0.349948	-2.9694	0.002025
44	-0.361385	-3.0665	0.001525
45	-0.371326	-3.1508	0.001186
46	-0.374816	-3.1804	0.001085
47	-0.375416	-3.1855	0.001068
48	-0.374183	-3.175	0.001103

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.950207	8.0628	0
2	-0.078121	-0.6629	0.254762
3	-0.010819	-0.0918	0.463555
4	0.113876	0.9663	0.168572
5	-0.012043	-0.1022	0.459446
6	-0.032004	-0.2716	0.393367
7	-0.017169	-0.1457	0.442289
8	-0.029975	-0.2543	0.399977
9	-0.011251	-0.0955	0.462104
10	-0.013239	-0.1123	0.455434
11	-0.041439	-0.3516	0.363075
12	-0.038972	-0.3307	0.37092
13	-0.095898	-0.8137	0.209243
14	-0.081454	-0.6912	0.245844
15	-0.002147	-0.0182	0.492758
16	0.044906	0.381	0.352148
17	0.053399	0.4531	0.325919
18	-0.030112	-0.2555	0.399528
19	-0.010624	-0.0901	0.46421
20	0.004597	0.039	0.484495
21	-0.005262	-0.0446	0.482255
22	0.002652	0.0225	0.491055
23	-0.016896	-0.1434	0.443201
24	-0.047434	-0.4025	0.344258
25	-0.087883	-0.7457	0.229134
26	-0.04499	-0.3818	0.351884
27	-0.020031	-0.17	0.432756
28	0.007621	0.0647	0.474311
29	-0.027739	-0.2354	0.407295
30	-0.031905	-0.2707	0.393689
31	-0.011637	-0.0987	0.460809
32	-0.025784	-0.2188	0.413718
33	-0.000913	-0.0077	0.49692
34	0.030787	0.2612	0.397327
35	-0.025801	-0.2189	0.413664
36	-0.029796	-0.2528	0.400562
37	-0.038966	-0.3306	0.37094
38	-0.051788	-0.4394	0.33083
39	-0.046198	-0.392	0.348107
40	0.037112	0.3149	0.376872
41	-0.011675	-0.0991	0.46068
42	-0.040769	-0.3459	0.365199
43	-0.006385	-0.0542	0.478471
44	-0.018223	-0.1546	0.438773
45	-0.023784	-0.2018	0.420316
46	0.030425	0.2582	0.398508
47	0.000861	0.0073	0.497096
48	0.010623	0.0901	0.464215

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/18/t1290102928e2cd183oc5ezwix/1adtl1290102985.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/18/t1290102928e2cd183oc5ezwix/1adtl1290102985.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/18/t1290102928e2cd183oc5ezwix/2l5a61290102985.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/18/t1290102928e2cd183oc5ezwix/2l5a61290102985.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; 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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