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Opgave6BIS Goudkoers te brussel (2)

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Wed, 05 May 2010 21:43:40 +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/May/05/t1273095888gk7y5hb5481w7sq.htm/, Retrieved Wed, 05 May 2010 23:44:50 +0200

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/May/05/t1273095888gk7y5hb5481w7sq.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:

Opgave6BIS eigen reeks: Goudkoers te brussel (2)

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

23100 22650 22440 22910 22980 22535 22300 22780 22780 23300 23800 24510 24660 24730 25070 24690 24880 23920 23880 23990 24590 23610 23580 23360 23910 23940 23060 22800 23020 22890 22780 22530 22290 22820 22480 22110 22000 22230 22260 22590 22820 22420 22230 21600 21000 21360 21640 21450 21710 21620 21800 21490 21670 22130 22050 22050 22140 22390 22220 21790 21510 21670 21745 21850 22105 22050 21670 21680 21800 21920 21980 22270 21740 21950 22010 21890 21920 22110 22340 22210 22240 21960 22220 22060 22090 21960 21940 21790 21710 21690 21710 21670 21640 21500 21290 21250 21580 21670 21620 21510 21360 21420 21470 21370 21370 21340 21130 21130 20990 21240 21320 21430 21390 21530 21510 21630 21560 21610 21560 21310 21340 21410 21550 21380 21600 21530 21560 21670 21540 21540 21550 21590 21420 21420 21370 21380 21210 21505 21365 21385 21350 21360 21530 21380 21630 22145 22 etc...

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	0.010949	0.1653	0.434418
2	-0.065927	-0.9955	0.16028
3	-0.077122	-1.1645	0.122717
4	0.068097	1.0282	0.152464
5	-0.013165	-0.1988	0.421306
6	0.003013	0.0455	0.481877
7	-0.08435	-1.2737	0.102042
8	-0.005597	-0.0845	0.46636
9	0.159967	2.4154	0.008252
10	-0.121923	-1.841	0.03346
11	0.000657	0.0099	0.496046
12	-0.069961	-1.0564	0.145954
13	0.049935	0.754	0.225815
14	-0.065733	-0.9925	0.160992
15	0.035884	0.5418	0.294231
16	-0.007657	-0.1156	0.45403
17	0.077812	1.1749	0.120623
18	-0.019171	-0.2895	0.386241
19	-0.10206	-1.5411	0.062342
20	0.027223	0.4111	0.34071
21	0.066704	1.0072	0.157452
22	-0.064357	-0.9718	0.166099
23	-0.032077	-0.4843	0.314303
24	-0.003162	-0.0477	0.480982
25	0.063738	0.9624	0.168429
26	0.017543	0.2649	0.395663
27	-0.065825	-0.9939	0.160654
28	0.028795	0.4348	0.332061
29	0.056164	0.8481	0.198647
30	0.033344	0.5035	0.307555
31	-0.063317	-0.9561	0.170025
32	-0.022978	-0.347	0.364469
33	-0.040511	-0.6117	0.27067
34	0.021628	0.3266	0.372141
35	-0.076143	-1.1497	0.125728
36	-0.015269	-0.2306	0.408932
37	0.00412	0.0622	0.475223
38	0.030697	0.4635	0.321716
39	0.00422	0.0637	0.474627
40	-0.006619	-0.0999	0.460236
41	0.003432	0.0518	0.479358
42	0.01433	0.2164	0.414446
43	0.09529	1.4388	0.075784
44	0.019261	0.2908	0.385722
45	0.022397	0.3382	0.367769
46	-0.0136	-0.2053	0.418741
47	-0.03348	-0.5055	0.306835
48	-0.071011	-1.0722	0.142371

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.010949	0.1653	0.434418
2	-0.066055	-0.9974	0.159813
3	-0.075969	-1.1471	0.126269
4	0.065818	0.9938	0.160678
5	-0.024771	-0.374	0.354365
6	0.006176	0.0933	0.46289
7	-0.077705	-1.1733	0.120947
8	-0.010487	-0.1583	0.437162
9	0.156481	2.3628	0.009489
10	-0.147114	-2.2214	0.013654
11	0.038175	0.5764	0.282448
12	-0.070257	-1.0609	0.144939
13	0.018149	0.274	0.39215
14	-0.056746	-0.8569	0.196214
15	0.018993	0.2868	0.38727
16	0.029259	0.4418	0.329528
17	0.046043	0.6952	0.243806
18	-0.032558	-0.4916	0.311735
19	-0.073938	-1.1164	0.132706
20	0.026113	0.3943	0.346866
21	0.062907	0.9499	0.171592
22	-0.106968	-1.6152	0.053827
23	0.029659	0.4478	0.327345
24	-0.037369	-0.5643	0.286567
25	0.070159	1.0594	0.145274
26	-0.02752	-0.4155	0.339069
27	-0.036932	-0.5577	0.288812
28	0.082664	1.2482	0.106618
29	0.005498	0.083	0.466955
30	0.016976	0.2563	0.398964
31	-0.025705	-0.3881	0.349137
32	-0.029011	-0.438	0.330882
33	-0.030802	-0.4651	0.321154
34	-0.039708	-0.5996	0.27469
35	-0.041674	-0.6293	0.264904
36	-0.005695	-0.086	0.465771
37	-0.009411	-0.1421	0.443561
38	-0.004148	-0.0626	0.475059
39	0.022345	0.3374	0.368062
40	0.021829	0.3296	0.370999
41	-0.022012	-0.3324	0.369959
42	0.021344	0.3223	0.373764
43	0.090875	1.3722	0.085677
44	0.046447	0.7013	0.241906
45	0.002743	0.0414	0.483497
46	-0.021373	-0.3227	0.373602
47	-0.030174	-0.4556	0.324547
48	-0.055572	-0.8391	0.201139

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/05/t1273095888gk7y5hb5481w7sq/13x711273095818.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273095888gk7y5hb5481w7sq/13x711273095818.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273095888gk7y5hb5481w7sq/23x711273095818.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273095888gk7y5hb5481w7sq/23x711273095818.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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