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Autocorrelatiefunctie zonder differentiatie (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 06:48:46 -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/t126218100872diwcj5njnk63e.htm/, Retrieved Wed, 30 Dec 2009 14:50:10 +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/t126218100872diwcj5njnk63e.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	0.590905	5.014	2e-06
2	0.47484	4.0292	6.9e-05
3	0.275429	2.3371	0.01111
4	0.199917	1.6964	0.047069
5	0.217922	1.8491	0.034272
6	0.238187	2.0211	0.023495
7	0.170438	1.4462	0.076229
8	0.206584	1.7529	0.041936
9	0.102142	0.8667	0.194492
10	0.080548	0.6835	0.248251
11	0.057518	0.4881	0.313496
12	0.201814	1.7124	0.045559
13	0.130723	1.1092	0.135514
14	0.215114	1.8253	0.036052
15	0.105266	0.8932	0.187361
16	0.085745	0.7276	0.234619
17	0.126876	1.0766	0.142632
18	0.11171	0.9479	0.173178
19	0.075073	0.637	0.263068
20	0.079113	0.6713	0.252091
21	0.009307	0.079	0.468636
22	0.00309	0.0262	0.489577
23	0.016679	0.1415	0.443925
24	-0.042699	-0.3623	0.359091
25	-0.05435	-0.4612	0.323033
26	-0.025135	-0.2133	0.415856
27	-0.060938	-0.5171	0.303345
28	-0.033352	-0.283	0.388995
29	0.045329	0.3846	0.350824
30	-0.026627	-0.2259	0.410945
31	0.037168	0.3154	0.376693
32	-0.048387	-0.4106	0.341302
33	-0.090134	-0.7648	0.223441
34	-0.108183	-0.918	0.180851
35	-0.146049	-1.2393	0.109635
36	-0.15334	-1.3011	0.098681
37	-0.1313	-1.1141	0.134467
38	-0.135887	-1.153	0.126354
39	-0.177561	-1.5067	0.068137
40	-0.229377	-1.9463	0.027759
41	-0.213855	-1.8146	0.036874
42	-0.248348	-2.1073	0.019288
43	-0.16145	-1.3699	0.08748
44	-0.21375	-1.8137	0.036943
45	-0.143365	-1.2165	0.113884
46	-0.108469	-0.9204	0.180222
47	-0.141254	-1.1986	0.11731
48	-0.154861	-1.314	0.096502
49	-0.202359	-1.7171	0.045133
50	-0.169513	-1.4384	0.077332
51	-0.099596	-0.8451	0.200428
52	-0.09262	-0.7859	0.217251
53	-0.103804	-0.8808	0.190677
54	-0.122614	-1.0404	0.150815
55	-0.128316	-1.0888	0.139936
56	-0.118374	-1.0044	0.159267
57	-0.091189	-0.7738	0.220802
58	-0.063634	-0.54	0.295447
59	-0.055694	-0.4726	0.318971
60	-0.015393	-0.1306	0.448224

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.590905	5.014	2e-06
2	0.193094	1.6385	0.052845
3	-0.103864	-0.8813	0.19054
4	0.014903	0.1265	0.449861
5	0.155701	1.3212	0.095315
6	0.095095	0.8069	0.211189
7	-0.097193	-0.8247	0.206129
8	0.104951	0.8905	0.188072
9	-0.069441	-0.5892	0.278776
10	-0.032673	-0.2772	0.391196
11	0.016411	0.1393	0.444819
12	0.274428	2.3286	0.011346
13	-0.146161	-1.2402	0.109461
14	0.077078	0.654	0.257588
15	-0.042885	-0.3639	0.358502
16	-0.005629	-0.0478	0.481017
17	0.107878	0.9154	0.181524
18	-0.025972	-0.2204	0.413098
19	-0.070636	-0.5994	0.275406
20	-0.047956	-0.4069	0.342637
21	0.03018	0.2561	0.399308
22	-0.058804	-0.499	0.309662
23	0.088214	0.7485	0.228293
24	-0.167331	-1.4198	0.079984
25	-0.012932	-0.1097	0.456463
26	0.008873	0.0753	0.470095
27	0.028666	0.2432	0.404255
28	-0.019078	-0.1619	0.435926
29	0.13192	1.1194	0.13335
30	-0.14163	-1.2018	0.116696
31	0.032556	0.2763	0.391574
32	-0.064177	-0.5446	0.293868
33	-0.023652	-0.2007	0.420752
34	-0.065645	-0.557	0.289622
35	-0.119731	-1.016	0.156527
36	0.050344	0.4272	0.335261
37	-0.073772	-0.626	0.266655
38	0.086034	0.73	0.233872
39	-0.163854	-1.3903	0.084353
40	-0.061963	-0.5258	0.30033
41	-0.044617	-0.3786	0.353054
42	0.038176	0.3239	0.373465
43	-0.064858	-0.5503	0.291897
44	-0.032772	-0.2781	0.390873
45	0.065942	0.5595	0.288767
46	-0.000372	-0.0032	0.498746
47	-0.020195	-0.1714	0.432211
48	-0.072951	-0.619	0.268932
49	-0.057433	-0.4873	0.313752
50	0.046936	0.3983	0.345808
51	0.106382	0.9027	0.184852
52	-0.05795	-0.4917	0.312207
53	0.008975	0.0762	0.469752
54	-0.020918	-0.1775	0.42981
55	-0.00687	-0.0583	0.476837
56	0.07246	0.6148	0.270299
57	0.005134	0.0436	0.482687
58	-0.016987	-0.1441	0.442895
59	-0.041515	-0.3523	0.362833
60	0.05196	0.4409	0.330306

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/30/t126218100872diwcj5njnk63e/1so3j1262180923.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t126218100872diwcj5njnk63e/1so3j1262180923.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t126218100872diwcj5njnk63e/2xjpf1262180923.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/30/t126218100872diwcj5njnk63e/2xjpf1262180923.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 = 0 ; 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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