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Paper stationair maken ACF

*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, 19 Dec 2009 10:48:37 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/19/t1261245013b8xkfvglo6kr5c0.htm/, Retrieved Sat, 19 Dec 2009 18:50:15 +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/2009/Dec/19/t1261245013b8xkfvglo6kr5c0.htm/},
    year = {2009},
}
@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 = {2009},
    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:

ShwPaper stationair maken ACF

Dataseries X:

» Textbox « » Textfile « » CSV «

152.60 153.32 165.50 139.18 136.53 115.92 96.65 83.77 84.66 106.03 86.92 54.66 151.66 121.27 132.95 119.64 122.16 117.44 106.69 87.45 80.98 110.30 87.01 55.73 146.00 137.54 138.54 135.62 107.27 99.04 91.36 68.35 82.59 98.41 71.25 47.58 130.83 113.60 125.69 113.60 97.12 104.43 91.84 75.11 89.24 110.23 78.42 68.45 122.81 129.66 159.06 139.03 102.16 113.59 81.46 77.36 87.57 101.23 87.21 64.94 133.12 117.99 135.90 125.67 108.03 128.31 84.74 86.38 92.24 95.83 92.33 54.27

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	0.428305	3.6343	0.00026
2	0.207751	1.7628	0.041086
3	0.091352	0.7751	0.220395
4	-0.140199	-1.1896	0.11905
5	-0.265144	-2.2498	0.013759
6	-0.415727	-3.5276	0.000367
7	-0.330158	-2.8015	0.003264
8	-0.19458	-1.6511	0.05154
9	-0.051946	-0.4408	0.330349
10	0.024457	0.2075	0.418092
11	0.218462	1.8537	0.033938
12	0.697957	5.9224	0
13	0.283055	2.4018	0.009448
14	0.118183	1.0028	0.159654
15	0.04729	0.4013	0.344706
16	-0.154661	-1.3123	0.096787
17	-0.219168	-1.8597	0.033507
18	-0.343033	-2.9107	0.002398
19	-0.2932	-2.4879	0.007583
20	-0.144623	-1.2272	0.111878
21	-0.066833	-0.5671	0.286205
22	0.00825	0.07	0.472192
23	0.212655	1.8044	0.037672
24	0.571048	4.8455	4e-06
25	0.258514	2.1936	0.015748
26	0.114726	0.9735	0.166787
27	0.006255	0.0531	0.478908
28	-0.145375	-1.2335	0.110692
29	-0.188987	-1.6036	0.056589
30	-0.318276	-2.7007	0.004311
31	-0.25279	-2.145	0.017664
32	-0.117752	-0.9992	0.160531
33	-0.065927	-0.5594	0.28881
34	-0.021648	-0.1837	0.427388
35	0.111787	0.9485	0.173013
36	0.385584	3.2718	0.000821

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.428305	3.6343	0.00026
2	0.029767	0.2526	0.400656
3	-0.009474	-0.0804	0.468074
4	-0.22204	-1.8841	0.031796
5	-0.171512	-1.4553	0.074962
6	-0.281279	-2.3867	0.009814
7	-0.040307	-0.342	0.366668
8	0.005368	0.0456	0.481897
9	0.067052	0.569	0.285578
10	-0.060388	-0.5124	0.304968
11	0.135346	1.1484	0.127293
12	0.640549	5.4352	0
13	-0.447568	-3.7977	0.000151
14	-0.171043	-1.4513	0.075514
15	-0.041139	-0.3491	0.364026
16	0.029593	0.2511	0.401223
17	0.021971	0.1864	0.426317
18	0.088985	0.7551	0.226338
19	-0.034794	-0.2952	0.38433
20	-0.027454	-0.233	0.408228
21	-0.031998	-0.2715	0.393387
22	0.104036	0.8828	0.190148
23	0.144236	1.2239	0.112493
24	-0.069496	-0.5897	0.27862
25	-0.057085	-0.4844	0.314792
26	-0.030052	-0.255	0.399724
27	-0.143503	-1.2177	0.113664
28	0.118389	1.0046	0.159235
29	0.059841	0.5078	0.306585
30	-0.080052	-0.6793	0.249573
31	0.050579	0.4292	0.334537
32	-0.037914	-0.3217	0.374302
33	0.039832	0.338	0.368179
34	-0.071485	-0.6066	0.273021
35	-0.229693	-1.949	0.027595
36	-0.036506	-0.3098	0.378819

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/19/t1261245013b8xkfvglo6kr5c0/147yd1261244915.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t1261245013b8xkfvglo6kr5c0/147yd1261244915.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t1261245013b8xkfvglo6kr5c0/2ll4v1261244915.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t1261245013b8xkfvglo6kr5c0/2ll4v1261244915.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; 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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