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(P) ACF - Totale Productie

*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, 16 Dec 2008 04:56:43 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/16/t12294286949xoyrftbx2r1qtj.htm/, Retrieved Tue, 16 Dec 2008 12:58:19 +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/2008/Dec/16/t12294286949xoyrftbx2r1qtj.htm/},
    year = {2008},
}
@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 = {2008},
    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 «

101,5 100,7 110,6 96,8 100,0 104,8 86,8 92,0 100,2 106,6 102,1 93,7 97,6 96,9 105,6 102,8 101,7 104,2 92,7 91,9 106,5 112,3 102,8 96,5 101,0 98,9 105,1 103,0 99,0 104,3 94,6 90,4 108,9 111,4 100,8 102,5 98,2 98,7 113,3 104,6 99,3 111,8 97,3 97,7 115,6 111,9 107,0 107,1 100,6 99,2 108,4 103,0 99,8 115,0 90,8 95,9 114,4 108,2 112,6 109,1 105,0 105,0 118,5 103,7 112,5 116,6 96,6 101,9 116,5 119,3 115,4 108,5 111,5 108,8 121,8 109,6 112,2 119,6 104,1 105,3 115,0 124,1 116,8 107,5 115,6 116,2 116,3 119,0 111,9 118,6 106,9 103,2

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	0.019142	0.1712	0.432245
2	0.19063	1.705	0.046034
3	0.386521	3.4572	0.000439
4	-0.061837	-0.5531	0.290873
5	0.143601	1.2844	0.101354
6	0.147155	1.3162	0.095934
7	-0.231903	-2.0742	0.020638
8	-0.113527	-1.0154	0.156485
9	0.021626	0.1934	0.423556
10	-0.253361	-2.2661	0.013072
11	-0.109904	-0.983	0.164283
12	-0.121813	-1.0895	0.139597
13	-0.228132	-2.0405	0.022301
14	-0.020832	-0.1863	0.426329
15	0.012123	0.1084	0.456962
16	-0.119797	-1.0715	0.143584
17	0.08342	0.7461	0.228887
18	0.069662	0.6231	0.267504
19	-0.108677	-0.972	0.166982
20	0.198141	1.7722	0.040082
21	0.135332	1.2104	0.114836
22	-0.098096	-0.8774	0.191448
23	0.36586	3.2724	0.000788
24	-0.092232	-0.825	0.205926
25	-0.001122	-0.01	0.496008
26	0.213381	1.9085	0.029954
27	-0.105611	-0.9446	0.173849
28	-0.027794	-0.2486	0.402156
29	0.028546	0.2553	0.399565
30	-0.223697	-2.0008	0.024402
31	-0.028964	-0.2591	0.398127
32	0.025381	0.227	0.410497
33	-0.232221	-2.077	0.020503
34	0.000444	0.004	0.49842
35	-0.040941	-0.3662	0.357597
36	-0.113808	-1.0179	0.15589
37	0.102314	0.9151	0.181438
38	0.033088	0.2959	0.384018
39	-0.067039	-0.5996	0.275228
40	0.104802	0.9374	0.175692
41	0.063387	0.567	0.286167
42	-0.019783	-0.1769	0.430001
43	0.118256	1.0577	0.146686
44	0.067354	0.6024	0.274295
45	-0.137542	-1.2302	0.111111
46	0.087555	0.7831	0.217936
47	-0.068895	-0.6162	0.269751
48	-0.151509	-1.3551	0.089594
49	0.073957	0.6615	0.255099
50	-0.147932	-1.3231	0.094778
51	-0.083832	-0.7498	0.227784
52	0.008525	0.0763	0.469705
53	-0.084645	-0.7571	0.225611
54	0.011495	0.1028	0.459185
55	-0.001236	-0.0111	0.495605
56	-0.112966	-1.0104	0.157676
57	0.026105	0.2335	0.407988
58	0.025022	0.2238	0.411741
59	-0.053129	-0.4752	0.317969
60	0.016907	0.1512	0.44009

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.019142	0.1712	0.432245
2	0.190333	1.7024	0.046283
3	0.394349	3.5272	0.000349
4	-0.100151	-0.8958	0.18653
5	-0.010053	-0.0899	0.464289
6	0.038954	0.3484	0.364223
7	-0.239973	-2.1464	0.017436
8	-0.284926	-2.5485	0.006367
9	0.05434	0.486	0.314136
10	-0.004913	-0.0439	0.48253
11	-0.068276	-0.6107	0.271572
12	-0.091775	-0.8209	0.207082
13	0.00369	0.033	0.486876
14	0.048566	0.4344	0.332587
15	0.081124	0.7256	0.235102
16	-0.015588	-0.1394	0.444733
17	0.067779	0.6062	0.273039
18	0.044262	0.3959	0.34662
19	-0.196771	-1.76	0.041117
20	0.005162	0.0462	0.481646
21	0.200773	1.7958	0.038154
22	-0.085364	-0.7635	0.2237
23	0.207564	1.8565	0.033532
24	-0.142026	-1.2703	0.103826
25	-0.025866	-0.2314	0.408817
26	-0.036265	-0.3244	0.373253
27	0.020755	0.1856	0.4266
28	-0.011948	-0.1069	0.457582
29	-0.060388	-0.5401	0.295304
30	-0.148071	-1.3244	0.094573
31	0.061199	0.5474	0.29282
32	0.043021	0.3848	0.350705
33	-0.010092	-0.0903	0.464151
34	0.061061	0.5461	0.293243
35	0.037227	0.333	0.370016
36	-0.052299	-0.4678	0.320607
37	0.017464	0.1562	0.438135
38	0.008972	0.0802	0.468121
39	0.027825	0.2489	0.402047
40	-0.050831	-0.4546	0.325298
41	-0.060664	-0.5426	0.294458
42	0.025816	0.2309	0.408989
43	-0.016531	-0.1479	0.441415
44	0.022717	0.2032	0.419754
45	-0.030259	-0.2706	0.39368
46	-0.129548	-1.1587	0.125011
47	-0.037337	-0.334	0.369645
48	-0.103772	-0.9282	0.178057
49	0.053905	0.4821	0.315511
50	0.05252	0.4698	0.319904
51	0.094969	0.8494	0.199088
52	-0.090878	-0.8128	0.209361
53	0.053543	0.4789	0.316657
54	0.039471	0.353	0.362494
55	-0.085409	-0.7639	0.223582
56	-0.074478	-0.6661	0.253616
57	-0.048954	-0.4379	0.331336
58	-0.049139	-0.4395	0.330739
59	-0.073976	-0.6617	0.255045
60	-0.108018	-0.9661	0.168442

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t12294286949xoyrftbx2r1qtj/10alv1229428601.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t12294286949xoyrftbx2r1qtj/10alv1229428601.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t12294286949xoyrftbx2r1qtj/2yyxj1229428601.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t12294286949xoyrftbx2r1qtj/2yyxj1229428601.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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