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Autocorrelatie D=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: Fri, 24 Dec 2010 12:01:32 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv.htm/, Retrieved Fri, 24 Dec 2010 12:59:12 +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/2010/Dec/24/t12931919490yaiikeaov1m6kv.htm/},
    year = {2010},
}
@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 = {2010},
    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 «

5.715 4.575 4.621 4.413 4.280 4.024 4.336 4.144 3.764 4.248 4.215 4.871 4.946 4.490 4.851 4.591 4.279 4.191 4.285 4.516 4.197 4.404 4.373 5.307 5.320 4.356 4.484 4.210 4.018 3.912 3.972 3.886 3.892 4.242 4.134 4.743 5.116 4.823 5.489 4.263 4.221 4.076 3.715 3.715 3.784 4.141 3.968 4.767 5.019 4.343 4.853 4.154 4.035 3.996 4.734 3.778 3.887 3.953 3.987 4.436 4.803 4.672 4.560 4.289 3.961 3.943 3.932 3.816 3.834 4.130 4.467 4.447

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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.33952	2.6299	0.005417
2	0.112819	0.8739	0.192831
3	0.007042	0.0545	0.478341
4	-0.049351	-0.3823	0.351805
5	-0.169416	-1.3123	0.09721
6	-0.110581	-0.8566	0.197548
7	-0.06255	-0.4845	0.314893
8	-0.220398	-1.7072	0.046478
9	-0.066629	-0.5161	0.303838
10	-0.193676	-1.5002	0.069402
11	-0.378877	-2.9348	0.002362
12	-0.493982	-3.8264	0.000156
13	-0.059081	-0.4576	0.324433
14	0.140259	1.0864	0.140815
15	0.16801	1.3014	0.099049
16	0.359261	2.7828	0.003597
17	0.264597	2.0496	0.022393
18	0.169959	1.3165	0.096507
19	0.036391	0.2819	0.389503
20	-1.5e-05	-1e-04	0.499955
21	-0.017622	-0.1365	0.445943
22	-0.004051	-0.0314	0.487537
23	0.108599	0.8412	0.201786
24	0.060954	0.4722	0.319266
25	-0.12784	-0.9902	0.163015
26	-0.225774	-1.7488	0.042717
27	-0.134262	-1.04	0.151258
28	-0.233969	-1.8123	0.037471
29	-0.121165	-0.9385	0.175864
30	0.041429	0.3209	0.374699
31	0.147542	1.1429	0.128819
32	0.129848	1.0058	0.159276
33	0.073912	0.5725	0.284556
34	0.060334	0.4673	0.320973
35	0.01761	0.1364	0.445979
36	-0.034166	-0.2646	0.396095
37	0.074415	0.5764	0.283246
38	0.037842	0.2931	0.385219
39	0.008551	0.0662	0.473706
40	0.038435	0.2977	0.383475
41	-0.002907	-0.0225	0.491054
42	-0.176805	-1.3695	0.08797
43	-0.106705	-0.8265	0.205889
44	-0.04746	-0.3676	0.357224
45	-0.025794	-0.1998	0.421157
46	-0.001517	-0.0118	0.495331
47	0.040298	0.3121	0.378005
48	0.038288	0.2966	0.383907

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.33952	2.6299	0.005417
2	-0.002775	-0.0215	0.491461
3	-0.034391	-0.2664	0.395425
4	-0.046487	-0.3601	0.360023
5	-0.152972	-1.1849	0.120361
6	-0.003038	-0.0235	0.490652
7	-0.008746	-0.0677	0.473107
8	-0.229604	-1.7785	0.040194
9	0.078753	0.61	0.272077
10	-0.242263	-1.8766	0.032722
11	-0.354134	-2.7431	0.004006
12	-0.416165	-3.2236	0.001024
13	0.101904	0.7893	0.21651
14	0.133195	1.0317	0.153171
15	-0.010155	-0.0787	0.468782
16	0.18333	1.4201	0.080381
17	-0.002099	-0.0163	0.493542
18	-0.017259	-0.1337	0.447049
19	-0.141917	-1.0993	0.138018
20	-0.219304	-1.6987	0.047276
21	0.112464	0.8711	0.193574
22	-0.153986	-1.1928	0.118827
23	-0.126841	-0.9825	0.164898
24	0.013266	0.1028	0.459248
25	-0.066872	-0.518	0.303186
26	0.024558	0.1902	0.424888
27	0.133638	1.0352	0.152375
28	0.029027	0.2248	0.411432
29	0.070736	0.5479	0.292891
30	-0.066242	-0.5131	0.304879
31	-0.024729	-0.1915	0.424372
32	-0.128896	-0.9984	0.161042
33	-0.131279	-1.0169	0.156646
34	-0.068935	-0.534	0.297667
35	0.114436	0.8864	0.189467
36	-0.079447	-0.6154	0.270311
37	0.011601	0.0899	0.464348
38	-0.006335	-0.0491	0.480512
39	0.059827	0.4634	0.322371
40	-0.045063	-0.3491	0.364135
41	0.045643	0.3535	0.362458
42	-0.106155	-0.8223	0.207089
43	0.083148	0.6441	0.260996
44	-0.111007	-0.8599	0.196645
45	-0.112721	-0.8731	0.193037
46	-0.024719	-0.1915	0.424401
47	-0.003827	-0.0296	0.488223
48	-0.154221	-1.1946	0.118474

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/1pxvz1293192088.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/1pxvz1293192088.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/2ioc21293192088.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/2ioc21293192088.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/3ioc21293192088.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/24/t12931919490yaiikeaov1m6kv/3ioc21293192088.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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 (par8 != '') par8 <- as.numeric(par8)

ox <- x

if (par8 == '') {

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

} else {

x <- log(x,base=par8)

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='picts.png')

op <- par(mfrow=c(2,1))

plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')

if (par8=='') {

mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

} else {

mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

}

plot(x,type='l', main=mytitle,xlab='time',ylab='value')

par(op)

dev.off()

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)

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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