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paper autocorrelation adapted totale industrie

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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, 03 Dec 2008 08:17:29 -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/03/t122831754603bmz2idy0if7ea.htm/, Retrieved Wed, 03 Dec 2008 15:19:08 +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/03/t122831754603bmz2idy0if7ea.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

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

97.6 96 115.9 109.1 117.3 109.8 112.8 110.7 100 113.3 122.4 112.5 104.2 92.5 117.2 109.3 106.1 118.8 105.3 106 102 112.9 116.5 114.8 100.5 85.4 114.6 109.9 100.7 115.5 100.7 99 102.3 108.8 105.9 113.2 95.7 80.9 113.9 98.1 102.8 104.7 95.9 94.6 101.6 103.9 110.3 114.1 96.8 87.4 111.4 97.4 102.9 112.7 97 95.1 96.9 98.6 111.7 109.8 89.9 87.4 104.5 98.1 102.7 105.4 97 97.4 92 101.7 112.6 106.9 92.1 86 104.7 102 103.1 106 96.1 96.2 90.7 102.3

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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.025027	0.1906	0.424751
2	0.312657	2.3811	0.010282
3	0.227404	1.7319	0.044307
4	0.0455	0.3465	0.365103
5	0.218007	1.6603	0.051126
6	0.093431	0.7116	0.239797
7	-0.125264	-0.954	0.172025
8	-0.004298	-0.0327	0.487001
9	-0.088919	-0.6772	0.25049
10	-0.127888	-0.974	0.167059
11	-0.166685	-1.2694	0.104678
12	-0.388198	-2.9564	0.002247
13	-0.11359	-0.8651	0.195281
14	-0.271075	-2.0644	0.021729
15	-0.055352	-0.4216	0.337455
16	-0.108054	-0.8229	0.206963
17	-0.103923	-0.7915	0.215951
18	0.004794	0.0365	0.4855
19	-0.093455	-0.7117	0.239741
20	-0.05275	-0.4017	0.34468
21	0.164743	1.2546	0.107321
22	-0.147905	-1.1264	0.132315
23	0.20099	1.5307	0.065641
24	-0.019435	-0.148	0.441422
25	-0.022125	-0.1685	0.433388
26	0.202795	1.5444	0.06396
27	0.008679	0.0661	0.473764
28	-0.023434	-0.1785	0.429489
29	0.026898	0.2048	0.419204
30	-0.052946	-0.4032	0.344133
31	0.096179	0.7325	0.233413
32	0.077294	0.5887	0.27919
33	-0.067421	-0.5135	0.304789
34	0.076246	0.5807	0.281855
35	-0.021758	-0.1657	0.434483
36	0.076227	0.5805	0.281905

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.025027	0.1906	0.424751
2	0.312227	2.3778	0.010365
3	0.237495	1.8087	0.03784
4	-0.051508	-0.3923	0.348148
5	0.087547	0.6667	0.253791
6	0.06433	0.4899	0.313018
7	-0.251681	-1.9167	0.030101
8	-0.158525	-1.2073	0.11611
9	-0.01279	-0.0974	0.46137
10	-0.059287	-0.4515	0.326652
11	-0.18456	-1.4056	0.082594
12	-0.348229	-2.652	0.005151
13	0.034686	0.2642	0.396296
14	-0.020834	-0.1587	0.43724
15	0.113149	0.8617	0.196196
16	0.099913	0.7609	0.224895
17	0.124584	0.9488	0.173328
18	0.074085	0.5642	0.287391
19	-0.19944	-1.5189	0.067112
20	-0.21469	-1.635	0.053729
21	0.173472	1.3211	0.095824
22	-0.179604	-1.3678	0.088322
23	-0.068162	-0.5191	0.302832
24	-0.157945	-1.2029	0.116956
25	-0.066693	-0.5079	0.306719
26	0.08265	0.6294	0.265766
27	0.159424	1.2141	0.114808
28	0.025717	0.1959	0.422704
29	-0.020751	-0.158	0.437488
30	-0.01537	-0.1171	0.45361
31	0.040022	0.3048	0.380806
32	0.011668	0.0889	0.46475
33	-0.028957	-0.2205	0.413117
34	-0.027922	-0.2127	0.416172
35	0.041527	0.3163	0.376471
36	-0.140149	-1.0673	0.14512

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t122831754603bmz2idy0if7ea/1n0xo1228317447.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t122831754603bmz2idy0if7ea/1n0xo1228317447.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t122831754603bmz2idy0if7ea/2p1rh1228317447.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t122831754603bmz2idy0if7ea/2p1rh1228317447.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 36 ; par2 = 1.3 ; par3 = 0 ; par4 = 2 ; 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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