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IKO opgave 6bis oefening 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: Sun, 02 May 2010 08:57:10 +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/02/t1272790724hy9o2e1n4cmp4lf.htm/, Retrieved Sun, 02 May 2010 10:58:45 +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/02/t1272790724hy9o2e1n4cmp4lf.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:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

278.1 283.3 287 287.9 279.7 273.2 272.6 274.8 277.2 277.5 278.7 279 280.1 280.8 280.1 270.5 260 258.2 260.1 262.2 263.4 264.7 267.4 266.8 265.2 262.5 255 252.8 249.6 254.2 259.4 260.8 261.6 257.2 249.8 235.2 227.4 223.1 221.6 218.5 220.1 222.1 222.9 222.8 222.1 209 201.7 204.5 208.7 213 218.6 221.9 224.6 226.8 229.6 231.4 229.1 232.7 236.6 242.2 251.5 261.5 266.4 280.9 294.4 308.8 328.8 348.2 365.9 387.5 395.9 395.8

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.911676	7.7358	0
2	0.798324	6.774	0
3	0.675564	5.7324	0
4	0.5625	4.773	5e-06
5	0.459858	3.902	0.000106
6	0.371345	3.151	0.001186
7	0.297067	2.5207	0.006964
8	0.231391	1.9634	0.02673
9	0.173103	1.4688	0.073117
10	0.12249	1.0394	0.151057
11	0.068158	0.5783	0.282419
12	0.016596	0.1408	0.444202
13	-0.029381	-0.2493	0.401918
14	-0.069856	-0.5927	0.277604
15	-0.104217	-0.8843	0.189737
16	-0.13142	-1.1151	0.13425
17	-0.159074	-1.3498	0.090656
18	-0.18582	-1.5767	0.05962
19	-0.211634	-1.7958	0.038363
20	-0.238761	-2.026	0.023238
21	-0.265456	-2.2525	0.013671
22	-0.288632	-2.4491	0.008378
23	-0.303995	-2.5795	0.005968
24	-0.310375	-2.6336	0.005167
25	-0.306103	-2.5974	0.005692
26	-0.293167	-2.4876	0.007589
27	-0.282724	-2.399	0.009516
28	-0.282231	-2.3948	0.009616
29	-0.279015	-2.3675	0.010299
30	-0.274656	-2.3305	0.011292
31	-0.268302	-2.2766	0.012892
32	-0.256275	-2.1746	0.016475
33	-0.236703	-2.0085	0.024171
34	-0.213353	-1.8104	0.037206
35	-0.184733	-1.5675	0.06069
36	-0.15497	-1.315	0.096348
37	-0.130885	-1.1106	0.135219
38	-0.121034	-1.027	0.153928
39	-0.118222	-1.0031	0.159575
40	-0.119583	-1.0147	0.156824
41	-0.120436	-1.0219	0.155117
42	-0.119641	-1.0152	0.156708
43	-0.111516	-0.9462	0.173594
44	-0.095453	-0.8099	0.210321
45	-0.079976	-0.6786	0.249778
46	-0.063539	-0.5391	0.295726
47	-0.053659	-0.4553	0.325129
48	-0.04676	-0.3968	0.346354

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.911676	7.7358	0
2	-0.194426	-1.6498	0.051675
3	-0.101565	-0.8618	0.195828
4	-0.001768	-0.015	0.494037
5	-0.022017	-0.1868	0.426165
6	-0.002955	-0.0251	0.490032
7	0.001396	0.0118	0.49529
8	-0.028538	-0.2422	0.404676
9	-0.021561	-0.183	0.427674
10	-0.010513	-0.0892	0.464582
11	-0.079599	-0.6754	0.250786
12	-0.025828	-0.2192	0.413575
13	-0.012534	-0.1064	0.457797
14	-0.02673	-0.2268	0.410605
15	-0.019327	-0.164	0.435097
16	-0.011776	-0.0999	0.460341
17	-0.059958	-0.5088	0.306237
18	-0.03745	-0.3178	0.375788
19	-0.035437	-0.3007	0.382259
20	-0.058077	-0.4928	0.311826
21	-0.041083	-0.3486	0.364202
22	-0.028904	-0.2453	0.403478
23	-0.013173	-0.1118	0.455655
24	-0.006695	-0.0568	0.477429
25	0.005665	0.0481	0.480895
26	-0.003151	-0.0267	0.489373
27	-0.055825	-0.4737	0.318578
28	-0.084695	-0.7187	0.237337
29	0.004531	0.0384	0.484719
30	-0.020769	-0.1762	0.430302
31	-0.025123	-0.2132	0.415895
32	0.00074	0.0063	0.497502
33	0.0059	0.0501	0.480104
34	-0.014851	-0.126	0.450035
35	0.008728	0.0741	0.470584
36	-0.012289	-0.1043	0.458621
37	-0.041749	-0.3543	0.362093
38	-0.075903	-0.6441	0.260793
39	-0.037619	-0.3192	0.375245
40	-0.034829	-0.2955	0.384217
41	-0.02139	-0.1815	0.428241
42	-0.029876	-0.2535	0.400301
43	0.00109	0.0092	0.496324
44	0.011551	0.098	0.461098
45	-0.044167	-0.3748	0.354467
46	-0.013655	-0.1159	0.45404
47	-0.048572	-0.4121	0.340729
48	-0.02104	-0.1785	0.429403

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/02/t1272790724hy9o2e1n4cmp4lf/1a1ef1272790626.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/02/t1272790724hy9o2e1n4cmp4lf/1a1ef1272790626.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/02/t1272790724hy9o2e1n4cmp4lf/22sdi1272790626.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/02/t1272790724hy9o2e1n4cmp4lf/22sdi1272790626.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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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