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autocorrelatie d=2, 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, 17 Dec 2010 15:00:38 +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/17/t12925980701zzvww5ek1rfwdo.htm/, Retrieved Fri, 17 Dec 2010 16:01:13 +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/17/t12925980701zzvww5ek1rfwdo.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 «

1.3031 1.3241 1.2961 1.2865 1.2305 1.2101 1.2125 1.2350 1.2014 1.1992 1.1791 1.1832 1.2159 1.1922 1.2114 1.2614 1.2812 1.2786 1.2772 1.2815 1.2679 1.2765 1.3247 1.3191 1.3029 1.3234 1.3354 1.3651 1.3453 1.3534 1.3706 1.3638 1.4268 1.4485 1.4635 1.4587 1.4876 1.5189 1.5783 1.5633 1.5554 1.5757 1.5593 1.4660 1.4065 1.2759 1.2705 1.3954 1.2793 1.2694 1.3282 1.3230 1.4135 1.4042 1.4253 1.4322 1.4632 1.4713 1.5016 1.4318

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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.219112	-1.4861	0.072039
2	-0.174439	-1.1831	0.121424
3	0.074636	0.5062	0.307566
4	-0.209886	-1.4235	0.080668
5	0.215908	1.4644	0.074949
6	0.065912	0.447	0.328473
7	-0.19172	-1.3003	0.099987
8	-0.02674	-0.1814	0.428442
9	-0.025262	-0.1713	0.432356
10	-0.006795	-0.0461	0.481721
11	0.295132	2.0017	0.025619
12	-0.270992	-1.838	0.036266
13	-0.225425	-1.5289	0.066568
14	0.115431	0.7829	0.218852
15	0.098853	0.6705	0.252961
16	0.008441	0.0573	0.477296
17	0.06529	0.4428	0.329987
18	-0.023312	-0.1581	0.43753
19	-0.074833	-0.5075	0.307099
20	0.109368	0.7418	0.230999
21	-0.040155	-0.2723	0.393288
22	0.131989	0.8952	0.187673
23	-0.218418	-1.4814	0.072662
24	0.003644	0.0247	0.490195
25	0.16324	1.1072	0.136993
26	-0.029938	-0.2031	0.419995
27	0.018018	0.1222	0.451635
28	-0.098464	-0.6678	0.253795
29	-0.050296	-0.3411	0.367282
30	0.013751	0.0933	0.463049
31	0.004329	0.0294	0.488352
32	0.063195	0.4286	0.335103
33	0.023348	0.1584	0.437437
34	-0.145352	-0.9858	0.164688
35	0.095466	0.6475	0.26027
36	0.069868	0.4739	0.318919
37	-0.051621	-0.3501	0.363926
38	0.004277	0.029	0.488491
39	-0.060236	-0.4085	0.342387
40	0.029969	0.2033	0.419915
41	0.055059	0.3734	0.355272
42	0.035015	0.2375	0.406669
43	-0.003556	-0.0241	0.490431
44	-0.042757	-0.29	0.386562
45	-0.070828	-0.4804	0.316618
46	NA	NA	NA
47	NA	NA	NA
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.219112	-1.4861	0.072039
2	-0.233667	-1.5848	0.059931
3	-0.026351	-0.1787	0.42947
4	-0.263544	-1.7874	0.040228
5	0.124359	0.8434	0.201672
6	0.061609	0.4179	0.338999
7	-0.089189	-0.6049	0.274105
8	-0.132442	-0.8983	0.186862
9	-0.067728	-0.4594	0.324073
10	-0.083854	-0.5687	0.286154
11	0.23406	1.5875	0.059628
12	-0.192158	-1.3033	0.099482
13	-0.255911	-1.7357	0.044659
14	-0.146477	-0.9935	0.162843
15	0.138551	0.9397	0.176141
16	-0.142861	-0.9689	0.168824
17	0.057605	0.3907	0.348912
18	0.144502	0.9801	0.166092
19	0.029563	0.2005	0.420984
20	-0.052566	-0.3565	0.36154
21	-0.059482	-0.4034	0.344252
22	0.133231	0.9036	0.185454
23	-0.162791	-1.1041	0.137646
24	0.084913	0.5759	0.283743
25	0.010138	0.0688	0.472739
26	0.00133	0.009	0.496422
27	0.025406	0.1723	0.431974
28	-0.021745	-0.1475	0.441698
29	-0.093753	-0.6359	0.264009
30	0.011982	0.0813	0.46779
31	-0.008845	-0.06	0.476211
32	0.043942	0.298	0.383512
33	-0.031195	-0.2116	0.416688
34	0.046579	0.3159	0.376748
35	-0.038083	-0.2583	0.398666
36	-0.005311	-0.036	0.485711
37	-0.007241	-0.0491	0.480523
38	0.041297	0.2801	0.390332
39	-0.043152	-0.2927	0.385545
40	0.013905	0.0943	0.462638
41	0.041904	0.2842	0.388764
42	-0.008028	-0.0545	0.478406
43	0.029538	0.2003	0.421051
44	-0.022952	-0.1557	0.438489
45	0.034707	0.2354	0.407474
46	NA	NA	NA
47	NA	NA	NA
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/11h6i1292598035.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/11h6i1292598035.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/21h6i1292598035.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/21h6i1292598035.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/3c9ol1292598035.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925980701zzvww5ek1rfwdo/3c9ol1292598035.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 2 ; 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 (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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