Home » date » 2010 » Dec » 16 »

WS6, autocorrelatie met nt-seizoenaal differentiatie

*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: Thu, 16 Dec 2010 19:36:00 +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/16/t12925280740ui1f2x89m9e375.htm/, Retrieved Thu, 16 Dec 2010 20:34:34 +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/16/t12925280740ui1f2x89m9e375.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 «

313737 312276 309391 302950 300316 304035 333476 337698 335932 323931 313927 314485 313218 309664 302963 298989 298423 301631 329765 335083 327616 309119 295916 291413 291542 284678 276475 272566 264981 263290 296806 303598 286994 276427 266424 267153 268381 262522 255542 253158 243803 250741 280445 285257 270976 261076 255603 260376 263903 264291 263276 262572 256167 264221 293860 300713 287224 275902 271115 277509 279681

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	0.335893	2.6018	0.005832
2	-0.294888	-2.2842	0.012957
3	-0.397181	-3.0766	0.001576
4	-0.231097	-1.7901	0.039244
5	0.068392	0.5298	0.299115
6	0.202819	1.571	0.060718
7	0.04551	0.3525	0.362842
8	-0.20342	-1.5757	0.060179
9	-0.323853	-2.5086	0.007422
10	-0.2207	-1.7095	0.04626
11	0.304316	2.3572	0.010846
12	0.775638	6.0081	0
13	0.23198	1.7969	0.038692
14	-0.277391	-2.1487	0.017853
15	-0.340837	-2.6401	0.005274
16	-0.206279	-1.5978	0.057667
17	0.043372	0.336	0.369038
18	0.156035	1.2086	0.115772
19	0.033767	0.2616	0.39728
20	-0.176887	-1.3702	0.087872
21	-0.266927	-2.0676	0.021499
22	-0.158224	-1.2256	0.112569
23	0.238931	1.8508	0.034565
24	0.552502	4.2797	3.4e-05
25	0.136877	1.0602	0.146642
26	-0.245566	-1.9021	0.030978
27	-0.254656	-1.9726	0.02658
28	-0.140125	-1.0854	0.141043
29	0.054338	0.4209	0.337666
30	0.101349	0.785	0.217758
31	0.018053	0.1398	0.444628
32	-0.133938	-1.0375	0.151839
33	-0.173669	-1.3452	0.091806
34	-0.07219	-0.5592	0.28906
35	0.177527	1.3751	0.087104
36	0.328004	2.5407	0.006834
37	0.082855	0.6418	0.261725
38	-0.15318	-1.1865	0.120045
39	-0.166805	-1.2921	0.100644
40	-0.084045	-0.651	0.258763
41	0.043018	0.3332	0.370065
42	0.065402	0.5066	0.307145
43	0.03217	0.2492	0.402034
44	-0.047715	-0.3696	0.356491
45	-0.072592	-0.5623	0.288004
46	-0.02678	-0.2074	0.418186
47	0.080357	0.6224	0.268004
48	0.158068	1.2244	0.112796
49	0.041121	0.3185	0.375597
50	-0.081609	-0.6321	0.264849
51	-0.086749	-0.672	0.252095
52	-0.031883	-0.247	0.402888
53	0.034656	0.2684	0.394639
54	0.027853	0.2157	0.414959
55	0.007876	0.061	0.475778
56	-0.00365	-0.0283	0.488768
57	-0.003824	-0.0296	0.488234
58	-0.001689	-0.0131	0.494802
59	-0.000329	-0.0025	0.498988
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.335893	2.6018	0.005832
2	-0.459562	-3.5598	0.000367
3	-0.14039	-1.0875	0.140592
4	-0.189601	-1.4686	0.073576
5	0.033418	0.2589	0.398317
6	-0.030984	-0.24	0.405575
7	-0.11773	-0.9119	0.182727
8	-0.205043	-1.5883	0.058743
9	-0.273911	-2.1217	0.019001
10	-0.294301	-2.2796	0.013099
11	0.238992	1.8512	0.03453
12	0.576737	4.4674	1.8e-05
13	-0.238795	-1.8497	0.034642
14	0.186943	1.4481	0.076403
15	0.077681	0.6017	0.274815
16	-0.041082	-0.3182	0.375711
17	-0.084213	-0.6523	0.258346
18	-0.029557	-0.2289	0.409846
19	-0.003239	-0.0251	0.490034
20	-0.113594	-0.8799	0.191214
21	-0.030615	-0.2371	0.406677
22	-0.01559	-0.1208	0.452141
23	-0.160819	-1.2457	0.108859
24	-0.13875	-1.0748	0.143394
25	-0.065596	-0.5081	0.306622
26	-0.1041	-0.8064	0.211611
27	-0.038423	-0.2976	0.38351
28	-0.017425	-0.135	0.446544
29	0.026624	0.2062	0.418656
30	-0.130516	-1.011	0.158044
31	0.040902	0.3168	0.376239
32	-0.002501	-0.0194	0.492305
33	0.05028	0.3895	0.349156
34	0.022459	0.174	0.431238
35	-0.021835	-0.1691	0.433132
36	-0.142636	-1.1049	0.136817
37	0.119995	0.9295	0.178182
38	-0.013027	-0.1009	0.45998
39	-0.104461	-0.8092	0.210812
40	0.001567	0.0121	0.495178
41	-0.0354	-0.2742	0.392434
42	-0.026488	-0.2052	0.419064
43	-0.024313	-0.1883	0.425627
44	0.129753	1.0051	0.159452
45	0.013058	0.1011	0.459887
46	-0.055245	-0.4279	0.335119
47	-0.010664	-0.0826	0.467222
48	0.055601	0.4307	0.33412
49	-0.128016	-0.9916	0.162686
50	-0.006001	-0.0465	0.481539
51	0.028614	0.2216	0.412673
52	-0.022693	-0.1758	0.43053
53	-0.038507	-0.2983	0.383264
54	0.030556	0.2367	0.406852
55	-0.090069	-0.6977	0.244039
56	-0.05891	-0.4563	0.324905
57	-0.00562	-0.0435	0.482712
58	-0.019806	-0.1534	0.439293
59	-0.05906	-0.4575	0.324491
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/16/t12925280740ui1f2x89m9e375/1w1c11292528156.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t12925280740ui1f2x89m9e375/1w1c11292528156.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t12925280740ui1f2x89m9e375/2pstm1292528156.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t12925280740ui1f2x89m9e375/2pstm1292528156.ps (open in new window)

Parameters (Session):

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