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ACF huwelijken 2

*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: Sun, 19 Dec 2010 10:21:14 +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/19/t1292753987m2njggot0r426p6.htm/, Retrieved Sun, 19 Dec 2010 11:19:50 +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/19/t1292753987m2njggot0r426p6.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 «

3111 3995 5245 5588 10681 10516 7496 9935 10249 6271 3616 3724 2886 3318 4166 6401 9209 9820 7470 8207 9564 5309 3385 3706 2733 3045 3449 5542 10072 9418 7516 7840 10081 4956 3641 3970 2931 3170 3889 4850 8037 12370 6712 7297 10613 5184 3506 3810 2692 3073 3713 4555 7807 10869 9682 7704 9826 5456 3677 3431 2765 3483 3445 6081 8767 9407 6551 12480 9530 5960 3252 3717 2642 2989 3607 5366 8898 9435 7328 8594 11349 5797 3621 3851

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	16 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.594048	-5.0055	2e-06
2	0.039851	0.3358	0.36901
3	0.028152	0.2372	0.406588
4	0.093928	0.7915	0.215658
5	-0.113598	-0.9572	0.170858
6	0.049149	0.4141	0.34001
7	0.050352	0.4243	0.336325
8	-0.13441	-1.1326	0.130605
9	0.112034	0.944	0.174181
10	0.009049	0.0762	0.469718
11	0.081598	0.6876	0.246985
12	-0.486729	-4.1013	5.4e-05
13	0.629675	5.3057	1e-06
14	-0.272003	-2.2919	0.012439
15	-0.015326	-0.1291	0.448807
16	-0.020026	-0.1687	0.433239
17	0.08809	0.7423	0.230189
18	-0.077679	-0.6545	0.25744
19	0.025819	0.2176	0.414199
20	0.055051	0.4639	0.32208
21	-0.091036	-0.7671	0.222788
22	0.003089	0.026	0.489653
23	0.115225	0.9709	0.167446
24	0.005688	0.0479	0.480955
25	-0.358183	-3.0181	0.001765
26	0.49276	4.1521	4.5e-05
27	-0.250327	-2.1093	0.019223
28	0.009996	0.0842	0.466556
29	0.024372	0.2054	0.41894
30	0.002265	0.0191	0.492412
31	-0.006177	-0.052	0.47932
32	-0.003199	-0.027	0.489287
33	0.041408	0.3489	0.364095
34	-0.057409	-0.4837	0.31503
35	0.016991	0.1432	0.44328
36	-0.005218	-0.044	0.482527
37	0.122406	1.0314	0.152924
38	-0.30087	-2.5352	0.006722
39	0.298532	2.5155	0.007076
40	-0.098169	-0.8272	0.205451
41	-0.029041	-0.2447	0.403697
42	0.016188	0.1364	0.445944
43	0.003285	0.0277	0.488997
44	-0.009322	-0.0785	0.468807
45	-0.005203	-0.0438	0.482579
46	0.042163	0.3553	0.361721
47	-0.030978	-0.261	0.397415
48	-0.0261	-0.2199	0.413282

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.594048	-5.0055	2e-06
2	-0.483756	-4.0762	5.9e-05
3	-0.452108	-3.8095	0.000147
4	-0.275174	-2.3187	0.011649
5	-0.275157	-2.3185	0.011653
6	-0.244808	-2.0628	0.021396
7	-0.068698	-0.5789	0.282257
8	-0.186263	-1.5695	0.060492
9	-0.165778	-1.3969	0.083402
10	-0.055704	-0.4694	0.320121
11	0.465499	3.9224	1e-04
12	-0.342511	-2.886	0.002582
13	-0.161916	-1.3643	0.088387
14	-0.093593	-0.7886	0.216478
15	0.035529	0.2994	0.382765
16	0.032056	0.2701	0.393931
17	-0.01912	-0.1611	0.436232
18	-0.053225	-0.4485	0.327587
19	-0.083425	-0.703	0.242192
20	-0.132504	-1.1165	0.133987
21	0.022603	0.1905	0.424748
22	-0.12692	-1.0694	0.144246
23	0.050592	0.4263	0.335592
24	-0.077217	-0.6506	0.258688
25	-0.283358	-2.3876	0.009811
26	0.060169	0.507	0.306866
27	0.052843	0.4453	0.328743
28	-0.064187	-0.5409	0.295151
29	-0.021898	-0.1845	0.427069
30	-0.189156	-1.5939	0.057705
31	-0.036569	-0.3081	0.379441
32	-0.015119	-0.1274	0.449494
33	0.029709	0.2503	0.401526
34	0.006834	0.0576	0.47712
35	0.185716	1.5649	0.06103
36	-0.075931	-0.6398	0.262178
37	-0.095058	-0.801	0.212909
38	0.085257	0.7184	0.237437
39	-0.021278	-0.1793	0.429111
40	-0.085099	-0.7171	0.237847
41	-0.034087	-0.2872	0.38739
42	-0.044236	-0.3727	0.355226
43	0.09358	0.7885	0.21651
44	-0.011002	-0.0927	0.463199
45	-0.009939	-0.0838	0.466745
46	-0.095152	-0.8018	0.212682
47	0.031724	0.2673	0.395001
48	-0.110737	-0.9331	0.176969

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/1bytx1292754057.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/1bytx1292754057.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/2lpa01292754057.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/2lpa01292754057.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/3lpa01292754057.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753987m2njggot0r426p6/3lpa01292754057.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; 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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