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deel1 acf D=d=0

*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, 16 Dec 2009 12:17:58 -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/16/t1260991110q6b0m9k59m3xh3f.htm/, Retrieved Wed, 16 Dec 2009 20:18:32 +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/16/t1260991110q6b0m9k59m3xh3f.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 «

627 696 825 677 656 785 412 352 839 729 696 641 695 638 762 635 721 854 418 367 824 687 601 676 740 691 683 594 729 731 386 331 707 715 657 653 642 643 718 654 632 731 392 344 792 852 649 629 685 617 715 715 629 916 531 357 917 828 708 858 775 785 1006 789 734 906 532 387 991 841

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.178546	1.4938	0.069858
2	-0.324786	-2.7174	0.004143
3	0.041262	0.3452	0.36548
4	-0.019466	-0.1629	0.435548
5	-0.105502	-0.8827	0.190211
6	0.037588	0.3145	0.377044
7	-0.076442	-0.6396	0.262274
8	-0.015635	-0.1308	0.448149
9	0.020574	0.1721	0.431913
10	-0.283913	-2.3754	0.010137
11	0.109874	0.9193	0.180556
12	0.756796	6.3318	0
13	0.111704	0.9346	0.176608
14	-0.320903	-2.6849	0.004526
15	-0.009377	-0.0785	0.468845
16	-0.03718	-0.3111	0.378335
17	-0.118814	-0.9941	0.161806
18	-0.025067	-0.2097	0.417247
19	-0.098628	-0.8252	0.206037
20	-0.051326	-0.4294	0.334465
21	-0.025809	-0.2159	0.414832
22	-0.236322	-1.9772	0.025979
23	0.05159	0.4316	0.333668
24	0.583566	4.8825	3e-06
25	0.121564	1.0171	0.156309
26	-0.295801	-2.4749	0.007877
27	-0.067551	-0.5652	0.286881
28	-0.040317	-0.3373	0.368442
29	-0.109689	-0.9177	0.180958
30	-0.022633	-0.1894	0.42518
31	-0.077669	-0.6498	0.258965
32	-0.08152	-0.682	0.24873
33	-0.006829	-0.0571	0.477299
34	-0.146586	-1.2264	0.112074
35	0.00862	0.0721	0.471357
36	0.425623	3.561	0.000335
37	0.086282	0.7219	0.236383
38	-0.243691	-2.0389	0.022621
39	-0.041806	-0.3498	0.363778
40	-0.006373	-0.0533	0.478814
41	-0.07981	-0.6677	0.253248
42	0.001269	0.0106	0.495778
43	-0.035691	-0.2986	0.383061
44	-0.035996	-0.3012	0.382092
45	0.024643	0.2062	0.418624
46	-0.09401	-0.7865	0.217101
47	-0.032679	-0.2734	0.39267
48	0.271363	2.2704	0.013132
49	0.055151	0.4614	0.322962
50	-0.151738	-1.2695	0.104228
51	0.002029	0.017	0.493252
52	-0.009173	-0.0767	0.469522
53	-0.060278	-0.5043	0.307811
54	0.009182	0.0768	0.469492
55	-0.027048	-0.2263	0.410812
56	-0.02984	-0.2497	0.401789
57	-0.001368	-0.0114	0.495451
58	-0.046433	-0.3885	0.349419
59	0.00082	0.0069	0.497273
60	0.143282	1.1988	0.117328

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.178546	1.4938	0.069858
2	-0.368409	-3.0823	0.001468
3	0.222766	1.8638	0.033273
4	-0.264133	-2.2099	0.015192
5	0.096744	0.8094	0.210509
6	-0.082024	-0.6863	0.247407
7	-0.103566	-0.8665	0.19459
8	0.099748	0.8346	0.203404
9	-0.17344	-1.4511	0.075609
10	-0.243108	-2.034	0.022872
11	0.366479	3.0662	0.00154
12	0.596746	4.9927	2e-06
13	-0.191751	-1.6043	0.056575
14	0.053439	0.4471	0.328092
15	-0.194366	-1.6262	0.054202
16	0.054685	0.4575	0.324355
17	-0.080684	-0.6751	0.250932
18	-0.128526	-1.0753	0.142961
19	-0.05346	-0.4473	0.328028
20	-0.14416	-1.2061	0.115915
21	-0.011673	-0.0977	0.461238
22	-0.008115	-0.0679	0.473031
23	-0.089359	-0.7476	0.228594
24	0.088608	0.7413	0.230481
25	0.029316	0.2453	0.403479
26	-0.021466	-0.1796	0.428994
27	-0.059295	-0.4961	0.31069
28	-0.041462	-0.3469	0.364857
29	-0.001732	-0.0145	0.494238
30	0.063685	0.5328	0.297922
31	-0.066439	-0.5559	0.290036
32	-0.06972	-0.5833	0.280778
33	0.088749	0.7425	0.230127
34	-0.02303	-0.1927	0.423883
35	-0.006307	-0.0528	0.479033
36	-0.155173	-1.2983	0.099227
37	-0.13383	-1.1197	0.133333
38	0.118703	0.9931	0.162031
39	-0.007873	-0.0659	0.473836
40	0.057695	0.4827	0.315402
41	-0.074319	-0.6218	0.268049
42	0.021453	0.1795	0.429036
43	0.116267	0.9728	0.167012
44	0.117268	0.9811	0.164952
45	-0.082969	-0.6942	0.244937
46	-0.024759	-0.2071	0.418248
47	-0.127691	-1.0683	0.144519
48	-0.071624	-0.5993	0.27547
49	-0.029191	-0.2442	0.403884
50	-0.000405	-0.0034	0.498654
51	0.035356	0.2958	0.384126
52	-0.050647	-0.4237	0.336526
53	-0.002584	-0.0216	0.491405
54	-0.040157	-0.336	0.368945
55	-0.02688	-0.2249	0.41136
56	-0.027477	-0.2299	0.409424
57	-0.098538	-0.8244	0.206247
58	0.051692	0.4325	0.333357
59	0.060331	0.5048	0.307655
60	-0.054525	-0.4562	0.324834

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260991110q6b0m9k59m3xh3f/1ycnm1260991076.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260991110q6b0m9k59m3xh3f/1ycnm1260991076.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260991110q6b0m9k59m3xh3f/2la331260991076.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260991110q6b0m9k59m3xh3f/2la331260991076.ps (open in new window)

Parameters (Session):

par1 = FALSE ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = 60 ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = 2 ; par9 = 1 ;

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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