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Autocorrelation function: totale consumptiegoederen

*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: Fri, 12 Dec 2008 04:19:03 -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/12/t1229081053ifza3f2aajduusa.htm/, Retrieved Fri, 12 Dec 2008 12:24:13 +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/2008/Dec/12/t1229081053ifza3f2aajduusa.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},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

98,5 97,0 103,3 99,6 100,1 102,9 95,9 94,5 107,4 116,0 102,8 99,8 109,6 103,0 111,6 106,3 97,9 108,8 103,9 101,2 122,9 123,9 111,7 120,9 99,6 103,3 119,4 106,5 101,9 124,6 106,5 107,8 127,4 120,1 118,5 127,7 107,7 104,5 118,8 110,3 109,6 119,1 96,5 106,7 126,3 116,2 118,8 115,2 110,0 111,4 129,6 108,1 117,8 122,9 100,6 111,8 127,0 128,6 124,8 118,5 114,7 112,6 128,7 111,0 115,8 126,0 111,1 113,2 120,1 130,6 124,0 119,4 116,7 116,5 119,6 126,5 111,3 123,5 114,2 103,7 129,5

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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.009277	0.0771	0.469401
2	0.080212	0.6663	0.253724
3	0.251083	2.0857	0.020355
4	-0.082314	-0.6838	0.248211
5	0.129196	1.0732	0.143464
6	0.17961	1.4919	0.070135
7	-0.112796	-0.937	0.176025
8	0.110708	0.9196	0.18049
9	0.245892	2.0425	0.022461
10	-0.117783	-0.9784	0.165652
11	-0.027622	-0.2294	0.409602
12	-0.115967	-0.9633	0.169381
13	-0.159121	-1.3218	0.095308
14	0.098368	0.8171	0.20834
15	-0.039412	-0.3274	0.372185
16	-0.096274	-0.7997	0.213312
17	0.153029	1.2712	0.103971
18	-0.01495	-0.1242	0.450767
19	-0.188452	-1.5654	0.061032
20	0.006105	0.0507	0.479851
21	0.011491	0.0955	0.462115
22	-0.120599	-1.0018	0.159977
23	0.16436	1.3653	0.088301
24	-0.245192	-2.0367	0.022759
25	-0.080398	-0.6678	0.253232
26	0.056467	0.4691	0.320255
27	0.01544	0.1283	0.449159
28	-0.083536	-0.6939	0.245038
29	0.035252	0.2928	0.385267
30	0.003779	0.0314	0.487525
31	0.071275	0.5921	0.277874
32	0.122686	1.0191	0.155856
33	-0.18109	-1.5042	0.068541
34	0.021311	0.177	0.430006
35	0.096439	0.8011	0.212917
36	0.01937	0.1609	0.436322

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.009277	0.0771	0.469401
2	0.080133	0.6656	0.253933
3	0.25129	2.0874	0.020275
4	-0.094533	-0.7852	0.217498
5	0.097103	0.8066	0.211334
6	0.139994	1.1629	0.124442
7	-0.099741	-0.8285	0.205118
8	0.033627	0.2793	0.390414
9	0.235357	1.955	0.027316
10	-0.093506	-0.7767	0.21999
11	-0.175227	-1.4555	0.075027
12	-0.201516	-1.6739	0.049337
13	-0.053948	-0.4481	0.327734
14	0.080258	0.6667	0.253602
15	0.000808	0.0067	0.497331
16	-0.004197	-0.0349	0.486146
17	0.155015	1.2876	0.101085
18	0.025974	0.2158	0.414908
19	-0.226722	-1.8833	0.031938
20	-0.04587	-0.381	0.352178
21	0.268082	2.2269	0.014612
22	-0.085544	-0.7106	0.239869
23	-0.063013	-0.5234	0.301179
24	-0.303302	-2.5194	0.007037
25	0.008402	0.0698	0.47228
26	-0.053093	-0.441	0.330287
27	0.251895	2.0924	0.020042
28	0.050363	0.4184	0.338495
29	0.115834	0.9622	0.169657
30	-0.045614	-0.3789	0.352964
31	-0.014938	-0.1241	0.450805
32	0.01354	0.1125	0.455389
33	-0.000216	-0.0018	0.499286
34	0.003961	0.0329	0.486925
35	0.019394	0.1611	0.436243
36	-0.057677	-0.4791	0.31669

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229081053ifza3f2aajduusa/1kque1229080735.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229081053ifza3f2aajduusa/1kque1229080735.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229081053ifza3f2aajduusa/2fv961229080735.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229081053ifza3f2aajduusa/2fv961229080735.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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