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acf voor diff

*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, 09 Dec 2009 02:48:55 -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/09/t12603521599fa30sa1a1akg2x.htm/, Retrieved Wed, 09 Dec 2009 10:49:21 +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/09/t12603521599fa30sa1a1akg2x.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 «

104.1 90.2 99.2 116.5 98.4 90.6 130.5 107.4 106 196.5 107.8 90.5 123.8 114.7 115.3 197 88.4 93.8 111.3 105.9 123.6 171 97 99.2 126.6 103.4 121.3 129.6 110.8 98.9 122.8 120.9 133.1 203.1 110.2 119.5 135.1 113.9 137.4 157.1 126.4 112.2 128.8 136.8 156.5 215.2 146.7 130.8 133.1 153.4 159.9 174.6 145 112.9 137.8 150.6 162.1 226.4 112.3 126.3

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	0.175752	1.3614	0.089244
2	-0.00025	-0.0019	0.499229
3	0.171358	1.3273	0.094714
4	-0.076924	-0.5958	0.276759
5	0.1522	1.1789	0.121539
6	0.588785	4.5607	1.3e-05
7	0.071725	0.5556	0.290281
8	-0.111972	-0.8673	0.194609
9	0.0874	0.677	0.250506
10	-0.051519	-0.3991	0.345633
11	0.128318	0.9939	0.16212
12	0.545737	4.2273	4.1e-05
13	0.022209	0.172	0.431995
14	-0.110066	-0.8526	0.198646
15	0.0282	0.2184	0.413916
16	-0.096946	-0.7509	0.227811
17	0.019736	0.1529	0.439506
18	0.319376	2.4739	0.008106
19	-0.023802	-0.1844	0.427172
20	-0.168376	-1.3042	0.098568
21	0.007726	0.0598	0.476238
22	-0.118172	-0.9154	0.181834
23	-0.013193	-0.1022	0.459472
24	0.355444	2.7533	0.003898
25	-0.063157	-0.4892	0.313238
26	-0.142076	-1.1005	0.137752
27	-0.067464	-0.5226	0.301599
28	-0.193493	-1.4988	0.069586
29	-0.081795	-0.6336	0.264381
30	0.141802	1.0984	0.138211
31	-0.089134	-0.6904	0.246293
32	-0.205828	-1.5943	0.058058
33	-0.106065	-0.8216	0.207285
34	-0.131758	-1.0206	0.155772
35	-0.055297	-0.4283	0.334972
36	0.189394	1.467	0.073794
37	-0.065889	-0.5104	0.305831
38	-0.179538	-1.3907	0.084728
39	-0.10443	-0.8089	0.210881
40	-0.124349	-0.9632	0.169656
41	-0.085682	-0.6637	0.254715
42	0.098917	0.7662	0.223279
43	-0.133482	-1.0339	0.152655
44	-0.180569	-1.3987	0.083528
45	-0.104872	-0.8123	0.209905
46	-0.107407	-0.832	0.204361
47	-0.054566	-0.4227	0.337024
48	0.057389	0.4445	0.329127
49	-0.122438	-0.9484	0.173364
50	-0.098082	-0.7597	0.225192
51	-0.04622	-0.358	0.360793
52	-0.084546	-0.6549	0.257521
53	-0.056095	-0.4345	0.332739
54	-0.044467	-0.3444	0.36586
55	-0.074959	-0.5806	0.281834
56	-0.068925	-0.5339	0.297695
57	-0.028567	-0.2213	0.412815
58	0.009525	0.0738	0.470715
59	0.001377	0.0107	0.495763
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.175752	1.3614	0.089244
2	-0.032132	-0.2489	0.402148
3	0.182882	1.4166	0.080886
4	-0.150869	-1.1686	0.123588
5	0.227655	1.7634	0.041461
6	0.533082	4.1292	5.7e-05
7	-0.102309	-0.7925	0.215602
8	-0.231801	-1.7955	0.038803
9	0.014697	0.1138	0.454872
10	0.107445	0.8323	0.204279
11	0.040036	0.3101	0.378772
12	0.263829	2.0436	0.022695
13	-0.096299	-0.7459	0.229313
14	-0.042714	-0.3309	0.370951
15	-0.101214	-0.784	0.218061
16	-0.018836	-0.1459	0.442243
17	-0.160312	-1.2418	0.109576
18	-0.057906	-0.4485	0.327689
19	0.059389	0.46	0.323581
20	0.011369	0.0881	0.46506
21	0.005219	0.0404	0.483944
22	-0.079375	-0.6148	0.270494
23	-0.026136	-0.2024	0.420125
24	0.188976	1.4638	0.074234
25	-0.082934	-0.6424	0.26153
26	-0.027924	-0.2163	0.414746
27	-0.142867	-1.1066	0.136432
28	-0.031762	-0.246	0.403252
29	-0.04862	-0.3766	0.353896
30	-0.151786	-1.1757	0.122173
31	0.012535	0.0971	0.461488
32	-0.019895	-0.1541	0.439023
33	-0.003982	-0.0308	0.487747
34	0.097372	0.7542	0.226826
35	-0.001607	-0.0124	0.495054
36	0.01749	0.1355	0.446345
37	-0.008979	-0.0695	0.472393
38	-0.023519	-0.1822	0.428029
39	0.018579	0.1439	0.443025
40	-0.011505	-0.0891	0.464643
41	-0.019843	-0.1537	0.43918
42	-0.001757	-0.0136	0.494593
43	-0.158132	-1.2249	0.112703
44	0.068287	0.5289	0.299398
45	-0.078659	-0.6093	0.272316
46	-0.012211	-0.0946	0.462478
47	-0.04363	-0.338	0.368288
48	-0.130063	-1.0075	0.158878
49	0.033441	0.259	0.398249
50	0.092685	0.7179	0.237792
51	0.097728	0.757	0.226008
52	-0.033853	-0.2622	0.397023
53	-0.045214	-0.3502	0.363698
54	-0.072032	-0.558	0.289474
55	0.106991	0.8288	0.205265
56	-0.034939	-0.2706	0.393799
57	-0.002859	-0.0221	0.491203
58	0.03157	0.2445	0.403824
59	0.121168	0.9386	0.175859
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/09/t12603521599fa30sa1a1akg2x/1a1uu1260352133.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/09/t12603521599fa30sa1a1akg2x/1a1uu1260352133.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/09/t12603521599fa30sa1a1akg2x/2d6il1260352133.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/09/t12603521599fa30sa1a1akg2x/2d6il1260352133.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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