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acf 2 laaggeschoolden

*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: Tue, 21 Dec 2010 19:26:54 +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/21/t1292959492kejho809li06o4q.htm/, Retrieved Tue, 21 Dec 2010 20:24:55 +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/21/t1292959492kejho809li06o4q.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 «

104708 101817 97898 95559 92822 90848 101141 105841 93647 90923 89130 90212 93196 91861 90593 89895 88819 87924 96906 101217 98709 98139 95529 98577 100772 100180 99200 96251 94514 93780 105192 107682 99687 99436 102049 102673 105813 105056 103916 103513 101893 102503 113149 116696 108500 107800 105941 108742 111680 111270 110698 108517 107127 107088 116321 125045 116779 122887 120162 123198 123610 122293 121289 119393 117494 116693 125062 127281 120195 119804 117113 119240 115823 116281 113816 114632 112987 111633 116721 114850 112797 105368 102524 101327 102612 98873 95993 93244 90403 88539 98106 96963 90781 89253 87794 89810 90864 89025 87621 87718 83433 84535 92223 91052 88456 88706 89137 94066 99258 100673 102269 100833 99314 101764 108242 108148 104761 103772 103737 111043 109906 109335 107247 105690 102755 102280 110590 109122 102803 101424 99138

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	-0.072526	-0.7878	0.216186
2	0.211977	2.3027	0.011525
3	0.055149	0.5991	0.275137
4	0.163505	1.7761	0.039145
5	0.131119	1.4243	0.078497
6	0.049686	0.5397	0.295201
7	0.071046	0.7718	0.220901
8	-0.02597	-0.2821	0.389176
9	0.114852	1.2476	0.107322
10	-0.01628	-0.1768	0.429965
11	0.062054	0.6741	0.250789
12	-0.307033	-3.3352	0.00057
13	0.039053	0.4242	0.336088
14	0.130012	1.4123	0.080247
15	-0.073979	-0.8036	0.211616
16	0.003044	0.0331	0.486841
17	-0.095207	-1.0342	0.151576
18	0.066031	0.7173	0.23731
19	0.016968	0.1843	0.42704
20	-0.016172	-0.1757	0.430425
21	-0.047532	-0.5163	0.303294
22	-0.113898	-1.2373	0.109225
23	-0.036475	-0.3962	0.34633
24	-0.17871	-1.9413	0.027304
25	-0.024947	-0.271	0.393434
26	-0.230229	-2.5009	0.006879
27	-0.075673	-0.822	0.206363
28	-0.085455	-0.9283	0.17758
29	-0.064136	-0.6967	0.243681
30	-0.166473	-1.8084	0.036548
31	-0.125861	-1.3672	0.08708
32	-0.069104	-0.7507	0.227176
33	0.032913	0.3575	0.360667
34	-0.050293	-0.5463	0.292937
35	0.074876	0.8134	0.208824
36	0.02413	0.2621	0.396842
37	0.062176	0.6754	0.250372
38	-0.085467	-0.9284	0.177544
39	0.049307	0.5356	0.296619
40	-0.06201	-0.6736	0.250942
41	0.034109	0.3705	0.355831
42	0.053844	0.5849	0.279868
43	0.020783	0.2258	0.410888
44	-0.01912	-0.2077	0.417913
45	-0.096612	-1.0495	0.148052
46	0.054683	0.594	0.276822
47	-0.093751	-1.0184	0.155287
48	-0.036917	-0.401	0.344564

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.072526	-0.7878	0.216186
2	0.207811	2.2574	0.012911
3	0.086574	0.9404	0.174458
4	0.136389	1.4816	0.070561
5	0.134412	1.4601	0.073462
6	0.010967	0.1191	0.452685
7	0.007156	0.0777	0.469088
8	-0.075964	-0.8252	0.205466
9	0.050853	0.5524	0.290856
10	-0.016176	-0.1757	0.430409
11	0.018122	0.1969	0.422138
12	-0.331756	-3.6038	0.00023
13	-0.057325	-0.6227	0.26734
14	0.267156	2.9021	0.002212
15	-1.2e-05	-1e-04	0.49995
16	-0.008723	-0.0948	0.462333
17	-0.026165	-0.2842	0.38837
18	0.036889	0.4007	0.344676
19	0.067314	0.7312	0.233047
20	-0.061785	-0.6712	0.251717
21	-0.038054	-0.4134	0.340043
22	-0.131756	-1.4312	0.077503
23	-0.101174	-1.099	0.136996
24	-0.330254	-3.5875	0.000244
25	-0.058255	-0.6328	0.264041
26	0.060206	0.654	0.25719
27	-0.066344	-0.7207	0.236264
28	-0.021305	-0.2314	0.408691
29	0.047712	0.5183	0.302615
30	-0.024918	-0.2707	0.393554
31	0.022866	0.2484	0.402134
32	-0.03524	-0.3828	0.351278
33	0.15748	1.7107	0.044885
34	-0.018543	-0.2014	0.420354
35	0.093604	1.0168	0.155664
36	-0.057118	-0.6205	0.268075
37	0.059731	0.6488	0.258849
38	-0.14986	-1.6279	0.053107
39	-0.158865	-1.7257	0.043508
40	-0.067078	-0.7287	0.233828
41	0.042894	0.4659	0.321057
42	0.041433	0.4501	0.326741
43	0.043498	0.4725	0.318717
44	-0.022126	-0.2404	0.405238
45	0.011525	0.1252	0.450291
46	-0.018684	-0.203	0.419758
47	-0.045216	-0.4912	0.312107
48	-0.126982	-1.3794	0.085194

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/21/t1292959492kejho809li06o4q/1ubu61292959612.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/21/t1292959492kejho809li06o4q/1ubu61292959612.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/21/t1292959492kejho809li06o4q/2ubu61292959612.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/21/t1292959492kejho809li06o4q/2ubu61292959612.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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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