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Autocorrelatie met differentiatie d=1 (import)

*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, 30 Dec 2009 06:51:16 -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/Dec/30/t1262181204ov1vhbbcsckbyjz.htm/, Retrieved Wed, 30 Dec 2009 14:53:26 +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/Dec/30/t1262181204ov1vhbbcsckbyjz.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 «

228 136 174 69 108 149 134 131 180 127 59 59 202 173 296 154 117 86 38 17 52 12 61 65 70 91 111 90 110 100 99 137 139 124 103 75 55 75 65 17 27 17 20 131 26 66 59 35 57 6 24 57 42 55 30 35 22 18 22 82 90 66 64 50 56 99 97 41 59 92 91 47

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	-0.314706	-2.6518	0.004935
2	0.079783	0.6723	0.251799
3	-0.082432	-0.6946	0.244791
4	-0.173863	-1.465	0.073669
5	-0.029996	-0.2527	0.400596
6	0.137477	1.1584	0.125291
7	-0.154724	-1.3037	0.098269
8	0.147038	1.239	0.109719
9	-0.06421	-0.541	0.295085
10	0.066701	0.562	0.287933
11	-0.229312	-1.9322	0.028661
12	0.162425	1.3686	0.087717
13	-0.208022	-1.7528	0.041974
14	0.149921	1.2633	0.105315
15	0.005978	0.0504	0.479983
16	-0.049068	-0.4135	0.340259
17	0.10565	0.8902	0.188177
18	0.081094	0.6833	0.248319
19	-0.040649	-0.3425	0.366489
20	0.073261	0.6173	0.269504
21	-0.059801	-0.5039	0.30795
22	-0.080393	-0.6774	0.250177
23	0.109557	0.9231	0.179529
24	-0.078548	-0.6619	0.255102
25	-0.073275	-0.6174	0.269463
26	0.072126	0.6077	0.272648
27	-0.080716	-0.6801	0.249319
28	-0.066901	-0.5637	0.287362
29	0.192398	1.6212	0.054707
30	-0.193054	-1.6267	0.054115
31	0.172897	1.4569	0.074783
32	-0.069167	-0.5828	0.280932
33	-0.010157	-0.0856	0.466019
34	0.048196	0.4061	0.342943
35	-0.022895	-0.1929	0.423787
36	-0.018713	-0.1577	0.43758
37	0.023893	0.2013	0.420511
38	0.065881	0.5551	0.290279
39	0.06369	0.5367	0.296589
40	-0.104399	-0.8797	0.191
41	0.070427	0.5934	0.27739
42	-0.17355	-1.4624	0.074028
43	0.090346	0.7613	0.224508
44	-0.078179	-0.6588	0.256093
45	0.01566	0.132	0.447697
46	0.095576	0.8053	0.211656
47	-0.010512	-0.0886	0.464833
48	0.023641	0.1992	0.421337
49	-0.066553	-0.5608	0.288355
50	-0.082985	-0.6992	0.243342
51	0.064235	0.5413	0.295015
52	0.028886	0.2434	0.404201
53	0.000773	0.0065	0.49741
54	0.015232	0.1283	0.449118
55	-0.020403	-0.1719	0.431995
56	-0.003365	-0.0284	0.488731
57	0.03886	0.3274	0.37215
58	-0.005102	-0.043	0.482916
59	-0.096073	-0.8095	0.210459
60	0.029623	0.2496	0.401806

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.314706	-2.6518	0.004935
2	-0.021374	-0.1801	0.428794
3	-0.070528	-0.5943	0.277108
4	-0.244585	-2.0609	0.021488
5	-0.188381	-1.5873	0.058441
6	0.078306	0.6598	0.255752
7	-0.146952	-1.2382	0.109853
8	-0.026984	-0.2274	0.410394
9	-0.038506	-0.3245	0.373272
10	0.060095	0.5064	0.307083
11	-0.279316	-2.3536	0.010684
12	-0.001815	-0.0153	0.493922
13	-0.165241	-1.3923	0.084081
14	-0.04806	-0.405	0.343363
15	-0.06064	-0.511	0.305483
16	-0.137955	-1.1624	0.124477
17	0.052087	0.4389	0.331036
18	0.07248	0.6107	0.271665
19	0.110208	0.9286	0.178114
20	0.0177	0.1491	0.440932
21	0.134427	1.1327	0.130576
22	-0.073566	-0.6199	0.268662
23	0.173268	1.46	0.074353
24	-0.049364	-0.4159	0.339351
25	-0.062167	-0.5238	0.301014
26	-0.016501	-0.139	0.444908
27	-0.052339	-0.441	0.330269
28	-0.128262	-1.0808	0.141732
29	0.095098	0.8013	0.212812
30	-0.050954	-0.4293	0.334487
31	0.083948	0.7074	0.24083
32	-0.027993	-0.2359	0.407104
33	-0.019762	-0.1665	0.434111
34	0.108042	0.9104	0.182852
35	-0.126818	-1.0686	0.144437
36	-0.010476	-0.0883	0.464954
37	-0.15275	-1.2871	0.101121
38	0.115659	0.9746	0.166543
39	0.037835	0.3188	0.375406
40	0.002359	0.0199	0.492098
41	-0.036541	-0.3079	0.379529
42	0.072968	0.6148	0.270314
43	0.026568	0.2239	0.411753
44	-0.071288	-0.6007	0.274983
45	0.071417	0.6018	0.274623
46	0.030057	0.2533	0.400396
47	0.094829	0.799	0.213464
48	-0.029677	-0.2501	0.40163
49	-0.051773	-0.4362	0.331991
50	-0.071075	-0.5989	0.275578
51	0.063296	0.5333	0.297731
52	-0.029104	-0.2452	0.403492
53	-0.040012	-0.3371	0.368501
54	-0.013806	-0.1163	0.453859
55	-0.04055	-0.3417	0.366802
56	-0.003489	-0.0294	0.488313
57	-0.032356	-0.2726	0.392963
58	0.041548	0.3501	0.363655
59	-0.090517	-0.7627	0.224082
60	-0.098512	-0.8301	0.204639

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/30/t1262181204ov1vhbbcsckbyjz/1rpxr1262181073.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t1262181204ov1vhbbcsckbyjz/1rpxr1262181073.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t1262181204ov1vhbbcsckbyjz/2gsef1262181073.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t1262181204ov1vhbbcsckbyjz/2gsef1262181073.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

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