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autocorrelatie functie

*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: Mon, 27 Dec 2010 08:37:45 +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/27/t1293438977f70hb1sfu9cpcks.htm/, Retrieved Mon, 27 Dec 2010 09:36:17 +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/27/t1293438977f70hb1sfu9cpcks.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:

D=0 en d=2

Dataseries X:

» Textbox « » Textfile « » CSV «

9119000 9166000 9218000 9283000 9367000 9448000 9508000 9557000 9590000 9613000 9638000 9673000 9709000 9738000 9768000 9795000 9811000 9822000 9830000 9837000 9847000 9852000 9856000 9856000 9853000 9858000 9862000 9870000 9902000 9938000 9967400 10004500 10045000 10084500 10115600 10136800 10157000 10181000 10203000 10226000 10252000 10287000 10333000 10376080.14 10421120.61 10478650 10547958 10625700 10708433 10788760

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.450199	3.1191	0.001533
2	-0.010737	-0.0744	0.470504
3	0.021445	0.1486	0.441254
4	-0.119751	-0.8297	0.20542
5	-0.145657	-1.0091	0.158984
6	-0.08893	-0.6161	0.270361
7	-0.035724	-0.2475	0.402786
8	0.111377	0.7716	0.222055
9	0.068378	0.4737	0.318917
10	-0.006226	-0.0431	0.482887
11	-0.05388	-0.3733	0.355288
12	-0.182496	-1.2644	0.106101
13	-0.014628	-0.1013	0.45985
14	0.104573	0.7245	0.236136
15	-0.028749	-0.1992	0.421482
16	0.051336	0.3557	0.361823
17	0.201163	1.3937	0.084914
18	0.071596	0.496	0.311069
19	-0.087801	-0.6083	0.272927
20	-0.096863	-0.6711	0.252692
21	-0.069681	-0.4828	0.315729
22	-0.122245	-0.8469	0.200617
23	-0.104121	-0.7214	0.23709
24	0.027982	0.1939	0.42355
25	0.032507	0.2252	0.411383
26	0.019076	0.1322	0.447704
27	0.080889	0.5604	0.288902
28	0.078869	0.5464	0.293653
29	-0.003519	-0.0244	0.490324
30	-0.061298	-0.4247	0.336481
31	-0.121495	-0.8417	0.202054
32	-0.131772	-0.9129	0.182918
33	-0.097199	-0.6734	0.251956
34	-0.067534	-0.4679	0.320991
35	-0.055209	-0.3825	0.351891
36	-0.062055	-0.4299	0.334586
37	-0.017182	-0.119	0.45287
38	-0.041416	-0.2869	0.387698
39	-0.137642	-0.9536	0.17253
40	-0.113513	-0.7864	0.217738
41	0.002497	0.0173	0.493134
42	0.077978	0.5402	0.295762
43	0.11066	0.7667	0.223514
44	0.06783	0.4699	0.320264
45	0.008569	0.0594	0.476453
46	-0.005719	-0.0396	0.484279
47	-0.003885	-0.0269	0.48932
48	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.450199	3.1191	0.001533
2	-0.267667	-1.8545	0.034912
3	0.20005	1.386	0.086078
4	-0.319883	-2.2162	0.015725
5	0.150301	1.0413	0.151473
6	-0.211137	-1.4628	0.07502
7	0.195299	1.3531	0.091186
8	-0.005831	-0.0404	0.483971
9	-0.03062	-0.2121	0.416448
10	0.023956	0.166	0.434439
11	-0.178224	-1.2348	0.111463
12	-0.036742	-0.2546	0.400078
13	0.19879	1.3773	0.087411
14	-0.101053	-0.7001	0.243618
15	0.040917	0.2835	0.389014
16	0.007779	0.0539	0.478622
17	0.194571	1.348	0.091989
18	-0.18719	-1.2969	0.100434
19	0.028672	0.1986	0.42169
20	-0.028537	-0.1977	0.422052
21	-0.029605	-0.2051	0.419178
22	-0.13948	-0.9663	0.169357
23	0.09344	0.6474	0.260238
24	-0.052224	-0.3618	0.359538
25	0.025113	0.174	0.431304
26	-0.008795	-0.0609	0.475832
27	0.067621	0.4685	0.320778
28	0.045513	0.3153	0.376941
29	-0.024136	-0.1672	0.433951
30	-0.09872	-0.684	0.248647
31	-0.143714	-0.9957	0.1622
32	0.048576	0.3365	0.368963
33	-0.100214	-0.6943	0.24542
34	-0.080215	-0.5557	0.290484
35	-0.030703	-0.2127	0.416225
36	0.008495	0.0589	0.476657
37	-0.037391	-0.2591	0.398351
38	-0.123046	-0.8525	0.199089
39	0.007497	0.0519	0.479395
40	-0.049548	-0.3433	0.366443
41	-0.006421	-0.0445	0.482352
42	0.062216	0.431	0.334182
43	-0.013522	-0.0937	0.462875
44	-0.02799	-0.1939	0.423527
45	-0.077226	-0.535	0.297548
46	0.048126	0.3334	0.370132
47	0.061465	0.4258	0.336063
48	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/149uq1293439061.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/149uq1293439061.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/2fjcb1293439061.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/2fjcb1293439061.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/3fjcb1293439061.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293438977f70hb1sfu9cpcks/3fjcb1293439061.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 2 ; 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 (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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