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cs.shw.ws8.v1.3

*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: Thu, 26 Nov 2009 11:34:10 -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/26/t12592606197ofyyx4h4385ax9.htm/, Retrieved Thu, 26 Nov 2009 19:37:01 +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/26/t12592606197ofyyx4h4385ax9.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 «

10570 10297 10635 10872 10296 10383 10431 10574 10653 10805 10872 10625 10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032 17696 17745 19394 20148 20108 18584 18441 18391 19178 18079 18483 19644 19195 19650

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	-0.084606	-0.6499	0.259148
2	-0.081544	-0.6263	0.266751
3	0.156409	1.2014	0.117198
4	0.066358	0.5097	0.306081
5	-0.18876	-1.4499	0.076191
6	-0.088691	-0.6812	0.24919
7	-0.073622	-0.5655	0.28694
8	-0.128472	-0.9868	0.163882
9	0.083768	0.6434	0.261219
10	-0.036623	-0.2813	0.38973
11	0.062945	0.4835	0.315268
12	-0.052466	-0.403	0.344202
13	-0.00718	-0.0552	0.478102
14	-0.048932	-0.3759	0.354187
15	-0.101087	-0.7765	0.220289
16	-0.142251	-1.0927	0.139494
17	-0.056263	-0.4322	0.3336
18	0.057563	0.4421	0.329999
19	-0.12552	-0.9641	0.169455
20	0.136456	1.0481	0.149424
21	0.025197	0.1935	0.423599
22	0.167987	1.2903	0.100984
23	0.017282	0.1327	0.447422
24	-0.02986	-0.2294	0.409692
25	0.01132	0.0869	0.465503
26	0.124654	0.9575	0.171115
27	-0.02383	-0.183	0.427697
28	-0.109878	-0.844	0.201043
29	0.116471	0.8946	0.187309
30	-0.079953	-0.6141	0.270745
31	-0.01043	-0.0801	0.468208
32	0.008459	0.065	0.474208
33	-0.033882	-0.2602	0.397789
34	-0.020601	-0.1582	0.437403
35	-0.026262	-0.2017	0.420415
36	-0.005746	-0.0441	0.482474
37	0.023946	0.1839	0.42735
38	-0.046212	-0.355	0.361942
39	0.041882	0.3217	0.374409
40	0.04118	0.3163	0.376442
41	-0.016556	-0.1272	0.449619
42	-0.009871	-0.0758	0.469909
43	0.002829	0.0217	0.491367
44	-0.041558	-0.3192	0.375346
45	-0.030867	-0.2371	0.406702
46	0.017628	0.1354	0.446377
47	0.039313	0.302	0.381868
48	-0.015862	-0.1218	0.451722
49	-0.005305	-0.0407	0.483817
50	0.012637	0.0971	0.461501
51	0.042363	0.3254	0.373016
52	-0.004152	-0.0319	0.487332
53	-0.055754	-0.4283	0.335014
54	0.050104	0.3849	0.350863
55	-0.008835	-0.0679	0.473062
56	-0.023835	-0.1831	0.427682
57	0.014452	0.111	0.455994
58	-0.005939	-0.0456	0.481886
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.084606	-0.6499	0.259148
2	-0.089341	-0.6862	0.247623
3	0.143499	1.1022	0.137417
4	0.087807	0.6745	0.251326
5	-0.158902	-1.2205	0.113556
6	-0.138984	-1.0676	0.145035
7	-0.148379	-1.1397	0.129504
8	-0.128072	-0.9837	0.164631
9	0.117478	0.9024	0.185266
10	-0.006411	-0.0492	0.480446
11	0.094185	0.7234	0.236131
12	-0.120494	-0.9255	0.17923
13	-0.11389	-0.8748	0.192613
14	-0.120299	-0.924	0.179615
15	-0.147338	-1.1317	0.131165
16	-0.147338	-1.1317	0.131164
17	-0.08472	-0.6507	0.258868
18	0.038016	0.292	0.385653
19	-0.114684	-0.8809	0.190971
20	0.053559	0.4114	0.341136
21	-0.098885	-0.7595	0.225275
22	0.098605	0.7574	0.225911
23	-0.031125	-0.2391	0.405938
24	-0.115378	-0.8862	0.189545
25	-0.050777	-0.39	0.348961
26	0.105932	0.8137	0.209551
27	0.066633	0.5118	0.305344
28	-0.020227	-0.1554	0.438531
29	0.011581	0.089	0.464709
30	-0.13617	-1.0459	0.149927
31	-0.103113	-0.792	0.215759
32	-0.046022	-0.3535	0.362486
33	-0.053561	-0.4114	0.341132
34	0.074272	0.5705	0.285255
35	-0.056945	-0.4374	0.331709
36	-0.009978	-0.0766	0.469583
37	0.05005	0.3844	0.351018
38	-0.102643	-0.7884	0.216806
39	0.105778	0.8125	0.209886
40	-0.051483	-0.3954	0.34697
41	0.074002	0.5684	0.285954
42	-0.013511	-0.1038	0.458847
43	-0.044095	-0.3387	0.36802
44	-0.076908	-0.5907	0.278475
45	-0.042432	-0.3259	0.372816
46	-0.00879	-0.0675	0.473199
47	0.026064	0.2002	0.421005
48	-0.030032	-0.2307	0.409181
49	-0.097742	-0.7508	0.227887
50	-0.039149	-0.3007	0.382346
51	0.002779	0.0213	0.49152
52	0.004569	0.0351	0.486061
53	0.005354	0.0411	0.483667
54	0.034635	0.266	0.395568
55	-0.005121	-0.0393	0.484378
56	0.016721	0.1284	0.44912
57	-0.019173	-0.1473	0.441711
58	-0.020919	-0.1607	0.436446
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/26/t12592606197ofyyx4h4385ax9/1imv71259260448.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t12592606197ofyyx4h4385ax9/1imv71259260448.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t12592606197ofyyx4h4385ax9/2cab81259260448.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t12592606197ofyyx4h4385ax9/2cab81259260448.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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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