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Method 1:ACF - d=D=0, lambda =1 - Totale industriële productie index met basis jaar = 2000 (periode 31/1 2004-2009)

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Fri, 27 Nov 2009 06:43:54 -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/Nov/27/t1259329530vrvsncvu42ujax2.htm/, Retrieved Fri, 27 Nov 2009 14:45:32 +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/Nov/27/t1259329530vrvsncvu42ujax2.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 «

95.1 97 112.7 102.9 97.4 111.4 87.4 96.8 114.1 110.3 103.9 101.6 94.6 95.9 104.7 102.8 98.1 113.9 80.9 95.7 113.2 105.9 108.8 102.3 99 100.7 115.5 100.7 109.9 114.6 85.4 100.5 114.8 116.5 112.9 102 106 105.3 118.8 106.1 109.3 117.2 92.5 104.2 112.5 122.4 113.3 100 110.7 112.8 109.8 117.3 109.1 115.9 96 99.8 116.8 115.7 99.4 94.3 91

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	0.106314	0.8303	0.204793
2	-0.180062	-1.4063	0.08235
3	0.027812	0.2172	0.414382
4	-0.040386	-0.3154	0.376759
5	0.248916	1.9441	0.02825
6	0.33776	2.638	0.005284
7	0.152076	1.1877	0.119768
8	-0.057511	-0.4492	0.327449
9	-0.076246	-0.5955	0.276855
10	-0.211807	-1.6543	0.051605
11	0.05793	0.4524	0.326276
12	0.622317	4.8605	4e-06
13	0.00354	0.0277	0.489016
14	-0.238898	-1.8659	0.033436
15	-0.068367	-0.534	0.297653
16	-0.101209	-0.7905	0.216158
17	0.143757	1.1228	0.132965
18	0.202317	1.5801	0.059623
19	0.026885	0.21	0.417192
20	-0.138784	-1.0839	0.141328
21	-0.131616	-1.028	0.154015
22	-0.269356	-2.1037	0.019766
23	0.019453	0.1519	0.43987
24	0.340164	2.6568	0.005028
25	-0.07083	-0.5532	0.291075
26	-0.256608	-2.0042	0.024749
27	-0.179473	-1.4017	0.083032
28	-0.103451	-0.808	0.211121
29	0.062454	0.4878	0.313726
30	0.078256	0.6112	0.271669
31	-0.024947	-0.1948	0.423083
32	-0.173715	-1.3568	0.089929
33	-0.166067	-1.297	0.099754
34	-0.164418	-1.2841	0.101974
35	-0.040409	-0.3156	0.37669
36	0.182082	1.4221	0.080044
37	-0.068589	-0.5357	0.297058
38	-0.194577	-1.5197	0.066877
39	-0.119505	-0.9334	0.177157
40	-0.046015	-0.3594	0.360274
41	0.040826	0.3189	0.37546
42	0.072434	0.5657	0.286828
43	0.003998	0.0312	0.487594
44	-0.058526	-0.4571	0.32461
45	-0.115427	-0.9015	0.185431
46	-0.02577	-0.2013	0.420579
47	0.027241	0.2128	0.416111
48	0.097839	0.7641	0.223862
49	-0.009161	-0.0715	0.471598
50	-0.09764	-0.7626	0.224324
51	-0.049521	-0.3868	0.350135
52	-0.028376	-0.2216	0.412673
53	0.018997	0.1484	0.441269
54	0.086183	0.6731	0.251709
55	0.009627	0.0752	0.470156
56	-0.022368	-0.1747	0.430947
57	-0.02171	-0.1696	0.432959
58	0.008169	0.0638	0.474667
59	0.045302	0.3538	0.362346
60	0.028693	0.2241	0.411714

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.106314	0.8303	0.204793
2	-0.193553	-1.5117	0.067888
3	0.074856	0.5846	0.280471
4	-0.093876	-0.7332	0.233123
5	0.305906	2.3892	0.009996
6	0.260725	2.0363	0.023033
7	0.249772	1.9508	0.02784
8	0.001564	0.0122	0.495146
9	-0.000994	-0.0078	0.496915
10	-0.384636	-3.0041	0.00193
11	-0.124642	-0.9735	0.167078
12	0.475133	3.7109	0.000224
13	-0.086725	-0.6773	0.250375
14	-0.035895	-0.2804	0.390078
15	-0.048446	-0.3784	0.353233
16	0.023544	0.1839	0.427355
17	-0.087645	-0.6845	0.248118
18	-0.07045	-0.5502	0.292086
19	-0.049093	-0.3834	0.351368
20	-0.095218	-0.7437	0.229964
21	0.008615	0.0673	0.473288
22	-0.144396	-1.1278	0.131917
23	0.036416	0.2844	0.388526
24	-0.131918	-1.0303	0.153465
25	0.067569	0.5277	0.299801
26	-0.0577	-0.4506	0.326921
27	-0.031989	-0.2498	0.401773
28	0.045708	0.357	0.361165
29	-0.027935	-0.2182	0.41401
30	-0.046818	-0.3657	0.357941
31	-0.034147	-0.2667	0.395302
32	-0.039219	-0.3063	0.380205
33	-0.097018	-0.7577	0.225764
34	0.134808	1.0529	0.148273
35	-0.176074	-1.3752	0.087052
36	0.009715	0.0759	0.469882
37	-0.071846	-0.5611	0.288381
38	0.115288	0.9004	0.185717
39	0.070029	0.5469	0.293207
40	0.045031	0.3517	0.363135
41	0.009041	0.0706	0.471968
42	0.001077	0.0084	0.496658
43	0.008501	0.0664	0.473641
44	0.030639	0.2393	0.405838
45	-0.080653	-0.6299	0.265549
46	-0.00458	-0.0358	0.485791
47	0.028013	0.2188	0.413771
48	-0.078894	-0.6162	0.270035
49	-0.055134	-0.4306	0.334134
50	0.031801	0.2484	0.40234
51	-0.031886	-0.249	0.402083
52	-0.08805	-0.6877	0.247127
53	-0.023045	-0.18	0.428881
54	0.054943	0.4291	0.334674
55	-0.062909	-0.4913	0.312477
56	0.034601	0.2702	0.393942
57	0.052966	0.4137	0.340281
58	-0.022168	-0.1731	0.431558
59	-0.053925	-0.4212	0.337556
60	-0.053689	-0.4193	0.338227

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259329530vrvsncvu42ujax2/13x6t1259329432.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259329530vrvsncvu42ujax2/13x6t1259329432.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259329530vrvsncvu42ujax2/2myqi1259329432.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259329530vrvsncvu42ujax2/2myqi1259329432.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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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