Home » date » 2009 » Nov » 25 »

Methode 1 d=0, D=1, lambda =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 12:28:04 -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/t1259177346le3qsa8zqg5pkcc.htm/, Retrieved Wed, 25 Nov 2009 20:29:08 +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/t1259177346le3qsa8zqg5pkcc.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 «

105.7 105.7 111.1 82.4 60 107.3 99.3 113.5 108.9 100.2 103.9 138.7 120.2 100.2 143.2 70.9 85.2 133 136.6 117.9 106.3 122.3 125.5 148.4 126.3 99.6 140.4 80.3 92.6 138.5 110.9 119.6 105 109 129.4 148.6 101.4 134.8 143.7 81.6 90.3 141.5 140.7 140.2 100.2 125.7 119.6 134.7 109 116.3 146.9 97.4 89.4 132.1 139.8 129 112.5 121.9 121.7 123.1

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	-0.019201	-0.133	0.447364
2	0.112835	0.7817	0.219102
3	0.123249	0.8539	0.198702
4	0.073175	0.507	0.307247
5	0.18556	1.2856	0.102376
6	0.179626	1.2445	0.109681
7	-0.183671	-1.2725	0.104661
8	0.047061	0.326	0.372902
9	-0.114542	-0.7936	0.215675
10	0.017013	0.1179	0.45333
11	0.03061	0.2121	0.416474
12	-0.344577	-2.3873	0.01048
13	-0.01816	-0.1258	0.450201
14	-0.006557	-0.0454	0.481977
15	-0.071045	-0.4922	0.312405
16	-0.043658	-0.3025	0.3818
17	-0.019262	-0.1334	0.447198
18	-0.175089	-1.2131	0.115523
19	0.124667	0.8637	0.196019
20	0.053454	0.3703	0.35638
21	0.149691	1.0371	0.152445
22	-0.146045	-1.0118	0.158347
23	0.166037	1.1503	0.127852
24	0.053019	0.3673	0.357494
25	0.107414	0.7442	0.230195
26	0.009032	0.0626	0.475183
27	0.033845	0.2345	0.407804
28	-0.023206	-0.1608	0.436474
29	0.058269	0.4037	0.344113
30	-0.089744	-0.6218	0.26852
31	-0.071737	-0.497	0.310726
32	-0.112392	-0.7787	0.219996
33	-0.050812	-0.352	0.363176
34	0.045083	0.3123	0.378065
35	-0.104855	-0.7265	0.235543
36	-0.081959	-0.5678	0.286399

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.019201	-0.133	0.447364
2	0.112508	0.7795	0.219762
3	0.129012	0.8938	0.187938
4	0.06862	0.4754	0.318326
5	0.167566	1.1609	0.125705
6	0.174466	1.2087	0.116343
7	-0.234313	-1.6234	0.055531
8	-0.061082	-0.4232	0.337024
9	-0.158997	-1.1016	0.138073
10	-0.012517	-0.0867	0.465628
11	0.031338	0.2171	0.41452
12	-0.309882	-2.1469	0.01844
13	0.051888	0.3595	0.360402
14	0.074839	0.5185	0.303245
15	0.050857	0.3523	0.363059
16	-0.060943	-0.4222	0.337372
17	0.102712	0.7116	0.240075
18	-0.058299	-0.4039	0.344038
19	-0.002231	-0.0155	0.493865
20	0.112961	0.7826	0.218848
21	0.147557	1.0223	0.155881
22	-0.181264	-1.2558	0.107628
23	0.174862	1.2115	0.115821
24	-0.034839	-0.2414	0.405149
25	-0.026944	-0.1867	0.426351
26	-0.04005	-0.2775	0.391304
27	-0.027527	-0.1907	0.424777
28	-0.010445	-0.0724	0.471305
29	-0.026722	-0.1851	0.426951
30	-0.144428	-1.0006	0.161012
31	-0.130676	-0.9054	0.184901
32	0.030075	0.2084	0.417913
33	0.089557	0.6205	0.268942
34	-0.038679	-0.268	0.394932
35	0.113318	0.7851	0.21813
36	0.021056	0.1459	0.442313

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259177346le3qsa8zqg5pkcc/1cvcm1259177283.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259177346le3qsa8zqg5pkcc/1cvcm1259177283.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259177346le3qsa8zqg5pkcc/23bgy1259177283.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259177346le3qsa8zqg5pkcc/23bgy1259177283.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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