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(Partial) Autocorrelation Function Prijsindexcijfers Grondstoffen

*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: Mon, 08 Dec 2008 11:09:31 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/08/t122875982742c57vqzu7s2pwj.htm/, Retrieved Mon, 08 Dec 2008 18:10:27 +0000

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/2008/Dec/08/t122875982742c57vqzu7s2pwj.htm/},
    year = {2008},
}
@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 = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

Feedback Forum:

2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply] 
test

Post a new message

Original text written by user:

d=1

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

101 104 99 105 107 111 117 119 127 128 135 132 136 143 142 153 145 138 148 152 169 169 161 174 179 191 190 182 175 181 197 194 197 216 221 218 230 227 204 197 199 208 191 202 211 224 224 231 244 235 250 266 288 283 295 312 334 348 383 407

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	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.203013	1.5594	0.062128
2	0.066302	0.5093	0.306229
3	0.150154	1.1534	0.126708
4	0.227746	1.7493	0.042715
5	0.046915	0.3604	0.359933
6	-0.041835	-0.3213	0.374544
7	0.219137	1.6832	0.048808
8	-0.016123	-0.1238	0.450929
9	-0.132012	-1.014	0.157361
10	0.087764	0.6741	0.251431
11	0.275752	2.1181	0.019195
12	-0.025595	-0.1966	0.42241
13	-0.119725	-0.9196	0.180756
14	-0.037614	-0.2889	0.386828
15	0.132308	1.0163	0.156823
16	-0.141926	-1.0902	0.140038
17	-0.185644	-1.426	0.079575
18	-0.056351	-0.4328	0.333356
19	-0.198989	-1.5285	0.065871
20	-0.151525	-1.1639	0.124578
21	-0.035466	-0.2724	0.393124
22	0.080357	0.6172	0.269728
23	-0.026172	-0.201	0.420684
24	-0.071736	-0.551	0.291853
25	0.127082	0.9761	0.166491
26	0.084321	0.6477	0.259851
27	0.003018	0.0232	0.490792
28	-0.027064	-0.2079	0.418017
29	-0.059012	-0.4533	0.326006
30	-0.086588	-0.6651	0.254289
31	-0.076756	-0.5896	0.278864
32	-0.017378	-0.1335	0.447133
33	0.040213	0.3089	0.379249
34	-0.065856	-0.5058	0.307424
35	0.021815	0.1676	0.43375
36	0.002084	0.016	0.49364

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.203013	1.5594	0.062128
2	0.026166	0.201	0.4207
3	0.137491	1.0561	0.147617
4	0.181651	1.3953	0.084079
5	-0.038652	-0.2969	0.383796
6	-0.077988	-0.599	0.275719
7	0.210222	1.6147	0.055851
8	-0.148951	-1.1441	0.128598
9	-0.119411	-0.9172	0.181382
10	0.157703	1.2113	0.115297
11	0.209758	1.6112	0.056238
12	-0.121407	-0.9325	0.177428
13	-0.067156	-0.5158	0.303949
14	-0.140066	-1.0759	0.143182
15	0.132277	1.016	0.15688
16	-0.111076	-0.8532	0.198503
17	-0.175908	-1.3512	0.090899
18	-0.092533	-0.7108	0.240016
19	-0.098289	-0.755	0.226634
20	0.054682	0.42	0.337998
21	0.075661	0.5812	0.281673
22	-0.032187	-0.2472	0.402794
23	0.109694	0.8426	0.201434
24	0.089357	0.6864	0.247586
25	0.100096	0.7689	0.222524
26	-0.040008	-0.3073	0.379844
27	0.020919	0.1607	0.436446
28	-0.018339	-0.1409	0.444229
29	-0.079953	-0.6141	0.270745
30	-0.109589	-0.8418	0.201658
31	-0.029802	-0.2289	0.409865
32	-0.048299	-0.371	0.355986
33	0.049863	0.383	0.351547
34	-0.04212	-0.3235	0.37372
35	0.022472	0.1726	0.431775
36	-0.116389	-0.894	0.187476

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t122875982742c57vqzu7s2pwj/1jwqa1228759766.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t122875982742c57vqzu7s2pwj/1jwqa1228759766.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t122875982742c57vqzu7s2pwj/2x51o1228759766.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t122875982742c57vqzu7s2pwj/2x51o1228759766.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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