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Opgave 6 Stap 1 BIS

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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: Wed, 17 Nov 2010 15:51:44 +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/17/t1290009057z55wi54euf7suyz.htm/, Retrieved Wed, 17 Nov 2010 16:50:59 +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/17/t1290009057z55wi54euf7suyz.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:

Gemiddelde consumptieprijzen van damesfietsen

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

361.58 363.19 363.61 364.14 365.51 365.51 365.5 365.5 364.59 364.63 364.54 363.67 365.22 369.05 370.45 370.46 370.46 370.58 370.58 370.22 370.21 370.29 370.29 370.2 370.2 372.55 374.51 375.58 375.75 375.75 375.75 375.69 375.76 377.5 377.51 377.74 369.82 373.1 374.55 375.01 374.81 375.31 375.31 375.39 375.59 376.26 377.18 377.26 377.26 381.87 387.09 387.14 388.78 389.16 389.16 389.42 389.49 388.97 388.97 389.09 389.09 391.76 390.96 391.76 392.8 393.06 393.06 393.26 393.87 394.47 394.57 394.57 394.57 399.57 406.13 407.03 409.46 409.9 409.9 410.14 410.54 410.69 410.79 410.97

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	0.954788	8.7508	0
2	0.908068	8.3226	0
3	0.860461	7.8863	0
4	0.81262	7.4478	0
5	0.765699	7.0177	0
6	0.718471	6.5849	0
7	0.670346	6.1438	0
8	0.622523	5.7055	0
9	0.576894	5.2873	0
10	0.532111	4.8769	3e-06
11	0.498791	4.5715	8e-06
12	0.471617	4.3224	2.1e-05
13	0.441839	4.0495	5.7e-05
14	0.415261	3.8059	0.000134
15	0.391748	3.5904	0.000277
16	0.367918	3.372	0.000565
17	0.345149	3.1633	0.001086
18	0.322352	2.9544	0.002032
19	0.299153	2.7418	0.003733
20	0.275294	2.5231	0.006758
21	0.252238	2.3118	0.011618
22	0.229179	2.1005	0.019343
23	0.203946	1.8692	0.03254
24	0.181761	1.6659	0.049733
25	0.153718	1.4088	0.081286
26	0.125825	1.1532	0.126049
27	0.098174	0.8998	0.185406
28	0.069743	0.6392	0.262215
29	0.040443	0.3707	0.355911
30	0.011192	0.1026	0.45927
31	-0.018615	-0.1706	0.432469
32	-0.048359	-0.4432	0.329375
33	-0.075046	-0.6878	0.246734
34	-0.099858	-0.9152	0.181349
35	-0.115986	-1.063	0.145408
36	-0.124582	-1.1418	0.128388
37	-0.146482	-1.3425	0.09152
38	-0.165217	-1.5142	0.066859
39	-0.178634	-1.6372	0.052664
40	-0.190814	-1.7488	0.041986
41	-0.202708	-1.8578	0.033347
42	-0.214277	-1.9639	0.026426
43	-0.225994	-2.0713	0.020701
44	-0.237201	-2.174	0.01626
45	-0.248398	-2.2766	0.012677
46	-0.258386	-2.3681	0.010087
47	-0.265771	-2.4358	0.008486
48	-0.26882	-2.4638	0.007894

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.954788	8.7508	0
2	-0.040203	-0.3685	0.356725
3	-0.034253	-0.3139	0.377174
4	-0.027953	-0.2562	0.399214
5	-0.015763	-0.1445	0.442738
6	-0.030344	-0.2781	0.390805
7	-0.037772	-0.3462	0.365034
8	-0.025033	-0.2294	0.409545
9	-0.004287	-0.0393	0.484376
10	-0.02017	-0.1849	0.426892
11	0.100398	0.9202	0.18006
12	0.043241	0.3963	0.346441
13	-0.05407	-0.4956	0.31075
14	0.013176	0.1208	0.452086
15	0.015528	0.1423	0.443584
16	-0.025182	-0.2308	0.409017
17	-0.012378	-0.1134	0.454974
18	-0.02043	-0.1872	0.425962
19	-0.018693	-0.1713	0.432189
20	-0.025506	-0.2338	0.407868
21	0.002934	0.0269	0.489306
22	-0.003283	-0.0301	0.488032
23	-0.04898	-0.4489	0.327325
24	0.017816	0.1633	0.435344
25	-0.074171	-0.6798	0.249253
26	-0.021125	-0.1936	0.423474
27	-0.021107	-0.1934	0.423537
28	-0.03069	-0.2813	0.389595
29	-0.037437	-0.3431	0.366186
30	-0.027943	-0.2561	0.39925
31	-0.03055	-0.28	0.390086
32	-0.023789	-0.218	0.413969
33	-0.003948	-0.0362	0.485609
34	-0.002337	-0.0214	0.49148
35	0.06492	0.595	0.276721
36	0.0506	0.4638	0.322011
37	-0.174683	-1.601	0.056566
38	0.008344	0.0765	0.469612
39	0.03223	0.2954	0.384212
40	-0.015196	-0.1393	0.444784
41	-0.030926	-0.2834	0.388768
42	-0.019886	-0.1823	0.427909
43	-0.013446	-0.1232	0.451109
44	-0.007373	-0.0676	0.473141
45	-0.007516	-0.0689	0.472623
46	0.018696	0.1714	0.432179
47	-0.018555	-0.1701	0.432686
48	0.015759	0.1444	0.442753

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/17/t1290009057z55wi54euf7suyz/16yft1290009101.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/17/t1290009057z55wi54euf7suyz/16yft1290009101.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/17/t1290009057z55wi54euf7suyz/26yft1290009101.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/17/t1290009057z55wi54euf7suyz/26yft1290009101.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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