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WS 8.1

*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: Wed, 25 Nov 2009 12:07:37 -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/25/t1259176130nipmtf4nigsts6h.htm/, Retrieved Wed, 25 Nov 2009 20:08:52 +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/25/t1259176130nipmtf4nigsts6h.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 «

1076.7 1035.9 1037 1154 1237.2 996.6 1238.2 1153.4 1268.1 1156 1144.5 1232.9 1055.2 1109.7 1079.8 1126.3 1196.8 1130.4 1183.6 1200.9 1426.6 1080.4 1325.4 1230 1125.9 1174.5 1151.9 1439.3 1344.3 1319.1 1257.6 1249.1 1397.1 1348 1548.2 1377.6 1402.9 1167.6 1392.9 1547 1420 1266.4 1280.8 1128.6 1449.5 1511.7 1548.3 1652 1650.5 1370.8 1653.3 1474.3 1418.8 1554.1 1156.6 1223.4 1337.5 1098.9 1037.6 1202.5

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.565471	4.3801	2.4e-05
2	0.513143	3.9748	9.6e-05
3	0.430054	3.3312	0.000742
4	0.317715	2.461	0.008374
5	0.361215	2.798	0.003452
6	0.291451	2.2576	0.013812
7	0.218754	1.6945	0.047681
8	0.148112	1.1473	0.127913
9	0.140776	1.0904	0.139938
10	0.052768	0.4087	0.342093
11	0.178919	1.3859	0.085453
12	0.288749	2.2366	0.014519
13	0.137605	1.0659	0.145373
14	0.200035	1.5495	0.063264
15	0.040714	0.3154	0.376787
16	0.138581	1.0734	0.143686
17	0.081289	0.6297	0.265654
18	0.017309	0.1341	0.446895
19	0.013801	0.1069	0.457611
20	-0.058257	-0.4513	0.326717
21	-0.059357	-0.4598	0.323668
22	-0.151344	-1.1723	0.122855
23	-0.129822	-1.0056	0.159323
24	-0.130306	-1.0093	0.158431
25	-0.141447	-1.0956	0.138806
26	-0.165315	-1.2805	0.102645
27	-0.230278	-1.7837	0.039762
28	-0.105395	-0.8164	0.208755
29	-0.21539	-1.6684	0.050223
30	-0.169964	-1.3165	0.096501
31	-0.199772	-1.5474	0.063509
32	-0.240129	-1.86	0.033892
33	-0.209811	-1.6252	0.054682
34	-0.260994	-2.0217	0.02384
35	-0.249878	-1.9355	0.02882
36	-0.190802	-1.4779	0.072327

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.565471	4.3801	2.4e-05
2	0.284288	2.2021	0.015757
3	0.098552	0.7634	0.224113
4	-0.041065	-0.3181	0.375762
5	0.154551	1.1971	0.117979
6	0.013486	0.1045	0.458576
7	-0.070965	-0.5497	0.292284
8	-0.089966	-0.6969	0.244287
9	0.053329	0.4131	0.34051
10	-0.09683	-0.75	0.22808
11	0.206994	1.6034	0.057052
12	0.282368	2.1872	0.016318
13	-0.187016	-1.4486	0.076325
14	-0.005439	-0.0421	0.483267
15	-0.16796	-1.301	0.099115
16	0.169258	1.3111	0.097416
17	-0.173357	-1.3428	0.092195
18	-0.09711	-0.7522	0.227433
19	0.007664	0.0594	0.47643
20	-0.003821	-0.0296	0.488242
21	0.013865	0.1074	0.457417
22	-0.095659	-0.741	0.2308
23	-0.094457	-0.7317	0.233612
24	-0.016138	-0.125	0.450468
25	-0.017204	-0.1333	0.447217
26	-0.046561	-0.3607	0.35981
27	-0.067049	-0.5194	0.302709
28	0.061365	0.4753	0.318137
29	-0.057688	-0.4468	0.328296
30	-0.035785	-0.2772	0.391295
31	-0.004783	-0.037	0.485285
32	-0.108449	-0.84	0.202109
33	-0.050378	-0.3902	0.348875
34	0.019641	0.1521	0.439794
35	-0.017586	-0.1362	0.446052
36	0.110749	0.8579	0.197192

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259176130nipmtf4nigsts6h/1f73q1259176055.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259176130nipmtf4nigsts6h/1f73q1259176055.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259176130nipmtf4nigsts6h/2wsgz1259176055.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259176130nipmtf4nigsts6h/2wsgz1259176055.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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