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WS8 Identifying Integration Processes

*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, 27 Nov 2009 10:21:03 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/27/t1259342494rd5fwgonx4r7gf5.htm/, Retrieved Fri, 27 Nov 2009 18:21:37 +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/Nov/27/t1259342494rd5fwgonx4r7gf5.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

7.1 6.9 6.8 7.5 7.6 7.8 8.0 8.1 8.2 8.3 8.2 8.0 7.9 7.6 7.6 8.3 8.4 8.4 8.4 8.4 8.6 8.9 8.8 8.3 7.5 7.2 7.4 8.8 9.3 9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8.0 8.2 8.1 8.1 8.0 7.9 7.9 8.0 8.0 7.9 8.0 7.7 7.2 7.5 7.3 7.0 7.0 7.0 7.2 7.3 7.1 6.8 6.4 6.1 6.5 7.7 7.9 7.5 6.9 6.6 6.9 7.7 8.0 8.0 7.7 7.3 7.4 8.1 8.3 8.2

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	0.249461	2.1748	0.01638
2	-0.196184	-1.7103	0.045646
3	-0.536536	-4.6774	6e-06
4	-0.443302	-3.8646	0.000116
5	-0.05716	-0.4983	0.309854
6	0.220622	1.9233	0.029091
7	0.356159	3.1049	0.001337
8	0.20699	1.8045	0.037558
9	-0.036701	-0.32	0.374942
10	-0.135578	-1.1819	0.120458
11	-0.108545	-0.9463	0.173505
12	-0.231747	-2.0203	0.023437
13	-0.021878	-0.1907	0.424624
14	0.146188	1.2744	0.103196
15	0.192054	1.6743	0.049093
16	0.069065	0.6021	0.274451
17	-0.089592	-0.781	0.218602
18	-0.08025	-0.6996	0.243155
19	-0.169425	-1.477	0.071902
20	0.044582	0.3887	0.349309
21	0.219496	1.9135	0.029724
22	0.067901	0.592	0.27782
23	-0.045885	-0.4	0.345135
24	-0.230151	-2.0064	0.024185
25	-0.036904	-0.3217	0.374274
26	0.105053	0.9158	0.181326
27	0.150205	1.3095	0.097162
28	0.023008	0.2006	0.420782
29	-0.085356	-0.7441	0.229549
30	-0.230245	-2.0072	0.02414
31	0.040546	0.3535	0.362358
32	0.149045	1.2993	0.098877
33	0.146259	1.2751	0.103086
34	0.071709	0.6251	0.266876
35	-0.1356	-1.1821	0.120419
36	-0.19674	-1.7151	0.045198

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.249461	2.1748	0.01638
2	-0.275563	-2.4023	0.009367
3	-0.467789	-4.0781	5.5e-05
4	-0.369166	-3.2183	0.000948
5	-0.220379	-1.9212	0.029227
6	-0.268919	-2.3444	0.010836
7	-0.185486	-1.617	0.055008
8	-0.183264	-1.5977	0.057135
9	-0.196828	-1.7159	0.045126
10	-0.052321	-0.4561	0.324801
11	0.096776	0.8437	0.20075
12	-0.265813	-2.3173	0.011591
13	-0.057018	-0.4971	0.310287
14	0.086713	0.7559	0.226009
15	-0.002467	-0.0215	0.49145
16	-0.114083	-0.9946	0.161555
17	-0.094618	-0.8249	0.206017
18	0.006454	0.0563	0.477639
19	-0.252388	-2.2003	0.015413
20	-0.036892	-0.3216	0.374313
21	0.165472	1.4426	0.076628
22	-0.118459	-1.0327	0.15251
23	0.059294	0.5169	0.303359
24	-0.116161	-1.0127	0.157215
25	0.066125	0.5765	0.283001
26	0.169369	1.4765	0.071967
27	0.171117	1.4918	0.06995
28	-0.097011	-0.8457	0.200182
29	-0.013632	-0.1188	0.452857
30	-0.120259	-1.0484	0.14889
31	-0.003384	-0.0295	0.488272
32	-0.06757	-0.5891	0.278785
33	0.04723	0.4117	0.340845
34	0.112674	0.9823	0.164543
35	0.084331	0.7352	0.232247
36	-0.158782	-1.3842	0.085169

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259342494rd5fwgonx4r7gf5/11odz1259342461.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259342494rd5fwgonx4r7gf5/11odz1259342461.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259342494rd5fwgonx4r7gf5/2oyp81259342461.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259342494rd5fwgonx4r7gf5/2oyp81259342461.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; 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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