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Partial Autocorrelation Function aangepast

*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: Sat, 18 Dec 2010 12:23:08 +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/Dec/18/t1292674856yumqbamw7mipdsh.htm/, Retrieved Sat, 18 Dec 2010 13:20:56 +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/Dec/18/t1292674856yumqbamw7mipdsh.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

37 30 47 35 30 43 82 40 47 19 52 136 80 42 54 66 81 63 137 72 107 58 36 52 79 77 54 84 48 96 83 66 61 53 30 74 69 59 42 65 70 100 63 105 82 81 75 102 121 98 76 77 63 37 35 23 40 29 37 51 20 28 13 22 25 13 16 13 16 17 9 17 25 14 8 7 10 7 10 3

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.400271	-3.5577	0.000318
2	0.020034	0.1781	0.429563
3	-0.166789	-1.4825	0.071099
4	0.04629	0.4114	0.340934
5	0.055048	0.4893	0.313
6	0.007138	0.0634	0.474786
7	0.029139	0.259	0.398158
8	-0.079331	-0.7051	0.241408
9	0.138564	1.2316	0.110879
10	-0.120327	-1.0695	0.144053
11	-0.09902	-0.8801	0.190736
12	0.172803	1.5359	0.064278
13	-0.026325	-0.234	0.407801
14	0.006912	0.0614	0.475583
15	-0.087963	-0.7818	0.218325
16	0.05104	0.4537	0.325661
17	-0.107422	-0.9548	0.171298
18	0.106605	0.9475	0.173131
19	0.070427	0.626	0.26657
20	-0.143628	-1.2766	0.102742
21	0.136164	1.2103	0.114895
22	-0.181552	-1.6137	0.055294
23	0.105286	0.9358	0.176112
24	-0.003936	-0.035	0.486092
25	0.141732	1.2597	0.105736
26	-0.189517	-1.6845	0.048019
27	0.026923	0.2393	0.405747
28	-0.074059	-0.6582	0.256146
29	0.104495	0.9288	0.177919
30	0.067527	0.6002	0.275048
31	-0.067397	-0.599	0.275432
32	0.041686	0.3705	0.355997
33	0.027407	0.2436	0.404087
34	-0.042041	-0.3737	0.354827
35	-0.043521	-0.3868	0.349964
36	-0.009321	-0.0828	0.467092
37	0.086905	0.7724	0.221084
38	-0.028488	-0.2532	0.400384
39	-0.028507	-0.2534	0.400319
40	-0.037129	-0.33	0.371134
41	0.103664	0.9214	0.179826
42	-0.081124	-0.721	0.236505
43	0.051781	0.4602	0.323304
44	-0.090501	-0.8044	0.211794
45	0.046525	0.4135	0.340171
46	0.001067	0.0095	0.496228
47	-0.043298	-0.3848	0.350694
48	0.082685	0.7349	0.232281

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.400271	-3.5577	0.000318
2	-0.166928	-1.4837	0.070935
3	-0.274685	-2.4415	0.008432
4	-0.189851	-1.6874	0.047732
5	-0.063115	-0.561	0.2882
6	-0.041738	-0.371	0.355824
7	0.025233	0.2243	0.411562
8	-0.040211	-0.3574	0.360872
9	0.140139	1.2456	0.1083
10	0.012773	0.1135	0.454949
11	-0.189076	-1.6805	0.048401
12	0.075634	0.6723	0.251692
13	0.043741	0.3888	0.349244
14	-0.024573	-0.2184	0.413836
15	-0.054753	-0.4867	0.313924
16	0.011963	0.1063	0.457795
17	-0.1379	-1.2257	0.111979
18	-0.071438	-0.635	0.263647
19	0.113853	1.012	0.157325
20	-0.070475	-0.6264	0.266431
21	0.041815	0.3717	0.35557
22	-0.092904	-0.8257	0.205716
23	0.006251	0.0556	0.477916
24	0.028507	0.2534	0.400318
25	0.145362	1.292	0.100061
26	-0.041394	-0.3679	0.356959
27	-0.042805	-0.3805	0.352313
28	-0.170548	-1.5159	0.066772
29	0.041255	0.3667	0.357419
30	0.080734	0.7176	0.237566
31	-0.038786	-0.3447	0.365605
32	0.093963	0.8352	0.203072
33	0.154205	1.3706	0.08719
34	0.049525	0.4402	0.330502
35	0.037044	0.3293	0.371416
36	0.024772	0.2202	0.41315
37	-0.040621	-0.361	0.359514
38	-0.032456	-0.2885	0.386868
39	-0.095848	-0.8519	0.198419
40	-0.011681	-0.1038	0.458788
41	0.124388	1.1056	0.136132
42	-0.106137	-0.9434	0.174186
43	0.024453	0.2173	0.414252
44	-0.058895	-0.5235	0.301057
45	-0.04425	-0.3933	0.347576
46	-0.016758	-0.1489	0.440988
47	-0.001269	-0.0113	0.495515
48	0.001142	0.0102	0.495962

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/1muij1292674985.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/1muij1292674985.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/2e3hl1292674985.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/2e3hl1292674985.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/3e3hl1292674985.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674856yumqbamw7mipdsh/3e3hl1292674985.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 (par8 != '') par8 <- as.numeric(par8)

ox <- x

if (par8 == '') {

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

} else {

x <- log(x,base=par8)

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='picts.png')

op <- par(mfrow=c(2,1))

plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')

if (par8=='') {

mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

} else {

mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

}

plot(x,type='l', main=mytitle,xlab='time',ylab='value')

par(op)

dev.off()

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)

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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