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*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 09:35:19 -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/t12593397756qpysyaip7rbt2u.htm/, Retrieved Fri, 27 Nov 2009 17:36:17 +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/t12593397756qpysyaip7rbt2u.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 «

274412 272433 268361 268586 264768 269974 304744 309365 308347 298427 289231 291975 294912 293488 290555 284736 281818 287854 316263 325412 326011 328282 317480 317539 313737 312276 309391 302950 300316 304035 333476 337698 335932 323931 313927 314485 313218 309664 302963 298989 298423 301631 329765 335083 327616 309119 295916 291413 291542 284678 276475 272566 264981 263290 296806 303598 286994 276427 266424 267153 268381 262522 255542 253158 243803 250741 280445 285257 270976 261076 255603 260376 263903 264291 263276 262572 256167 264221 293860

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	0.95682	7.8319	0
2	0.908667	7.4378	0
3	0.853835	6.9889	0
4	0.804395	6.5843	0
5	0.749731	6.1368	0
6	0.694824	5.6874	0
7	0.648192	5.3057	1e-06
8	0.596833	4.8853	3e-06
9	0.541837	4.4351	1.8e-05
10	0.472222	3.8653	0.000127
11	0.409275	3.3501	0.000665
12	0.340819	2.7897	0.003431
13	0.285133	2.3339	0.011304
14	0.227655	1.8634	0.033392
15	0.168893	1.3824	0.085713
16	0.102577	0.8396	0.202051
17	0.035796	0.293	0.385212
18	-0.026124	-0.2138	0.415664
19	-0.091248	-0.7469	0.22887
20	-0.155337	-1.2715	0.103976
21	-0.216156	-1.7693	0.040696
22	-0.254715	-2.0849	0.020445
23	-0.28984	-2.3724	0.010275
24	-0.334584	-2.7387	0.003948
25	-0.369427	-3.0239	0.001768
26	-0.392033	-3.2089	0.001023
27	-0.404368	-3.3099	0.000753
28	-0.41985	-3.4366	0.000508
29	-0.430697	-3.5254	0.000384
30	-0.442929	-3.6255	0.000279
31	-0.451396	-3.6948	0.000222
32	-0.456215	-3.7343	0.000195
33	-0.452441	-3.7034	0.000216
34	-0.444568	-3.6389	0.000267
35	-0.440047	-3.6019	0.000301
36	-0.430035	-3.52	0.000391

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.95682	7.8319	0
2	-0.080931	-0.6624	0.254979
3	-0.101547	-0.8312	0.204408
4	0.043285	0.3543	0.362113
5	-0.091832	-0.7517	0.22744
6	-0.03767	-0.3083	0.37939
7	0.083023	0.6796	0.249559
8	-0.107155	-0.8771	0.191783
9	-0.082374	-0.6743	0.251234
10	-0.184237	-1.508	0.068122
11	0.037669	0.3083	0.379391
12	-0.10086	-0.8256	0.205987
13	0.102563	0.8395	0.202084
14	-0.060141	-0.4923	0.312066
15	-0.106344	-0.8705	0.193578
16	-0.149596	-1.2245	0.112527
17	-0.033375	-0.2732	0.392775
18	-0.001895	-0.0155	0.493835
19	-0.06071	-0.4969	0.310432
20	-0.090303	-0.7392	0.231196
21	-0.018306	-0.1498	0.440669
22	0.132082	1.0811	0.141756
23	0.004009	0.0328	0.486959
24	-0.212438	-1.7389	0.043324
25	0.143176	1.1719	0.122685
26	0.071976	0.5892	0.27887
27	0.026153	0.2141	0.415571
28	-0.060008	-0.4912	0.31245
29	-0.003763	-0.0308	0.48776
30	-0.121345	-0.9932	0.162081
31	-0.026994	-0.221	0.412898
32	0.06589	0.5393	0.295721
33	0.083527	0.6837	0.248262
34	-0.045842	-0.3752	0.354336
35	-0.102696	-0.8406	0.20178
36	-0.069776	-0.5711	0.284908

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/27/t12593397756qpysyaip7rbt2u/16nwy1259339717.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t12593397756qpysyaip7rbt2u/16nwy1259339717.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t12593397756qpysyaip7rbt2u/2p49w1259339717.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t12593397756qpysyaip7rbt2u/2p49w1259339717.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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