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paper: (p)acf niet-gezuiverde investeringen

*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: Fri, 19 Dec 2008 08:58:05 -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/19/t1229702387l64haboygn6zc8n.htm/, Retrieved Fri, 19 Dec 2008 16:59:49 +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/19/t1229702387l64haboygn6zc8n.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 «

101.3 91.5 152.6 86.6 86.6 98.5 86.7 89.1 111 92.6 85.1 116.1 98.3 97.7 177.9 94.2 83.8 109.5 102.3 102.5 162.7 85.3 88.2 104.7 99.4 113.8 166.6 89.2 93.2 115 97.2 112.5 121.8 100.2 93.8 113.6 110.7 127.6 185.9 105.9 108 125.2 106.2 123.3 145.2 114.3 108.4 120.9 126.3 141.3 208.2 131.6 119.8 122.5 137.6 141 154.1 127 106.1 129.9

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	0.142074	1.1005	0.137755
2	-0.008901	-0.0689	0.472631
3	0.247958	1.9207	0.029764
4	-0.04547	-0.3522	0.362957
5	0.101045	0.7827	0.218444
6	0.616056	4.7719	6e-06
7	0.026491	0.2052	0.419057
8	-0.13798	-1.0688	0.144724
9	0.17253	1.3364	0.09323
10	-0.122451	-0.9485	0.17334
11	0.014788	0.1145	0.454594
12	0.611422	4.7361	7e-06
13	-0.022696	-0.1758	0.430522
14	-0.13194	-1.022	0.155441
15	0.100432	0.7779	0.21983
16	-0.136734	-1.0591	0.14689
17	-0.026694	-0.2068	0.418445
18	0.379745	2.9415	0.002318
19	-0.077142	-0.5975	0.276197
20	-0.168334	-1.3039	0.098623
21	0.035427	0.2744	0.392353
22	-0.172272	-1.3344	0.093556
23	-0.053373	-0.4134	0.340385
24	0.362852	2.8106	0.003334
25	-0.098242	-0.761	0.224824
26	-0.136929	-1.0607	0.14655
27	0.001439	0.0111	0.495572
28	-0.165771	-1.2841	0.10203
29	-0.07061	-0.5469	0.293223
30	0.200859	1.5558	0.062502
31	-0.103817	-0.8042	0.212239
32	-0.18153	-1.4061	0.082422
33	-0.062377	-0.4832	0.315367
34	-0.166058	-1.2863	0.101644
35	-0.089531	-0.6935	0.245335
36	0.201716	1.5625	0.061717
37	-0.121665	-0.9424	0.17488
38	-0.157896	-1.2231	0.113045
39	-0.032567	-0.2523	0.400849
40	-0.135021	-1.0459	0.149909
41	-0.089726	-0.695	0.244865
42	0.019445	0.1506	0.44039
43	-0.12548	-0.972	0.167486
44	-0.174131	-1.3488	0.091233
45	-0.078201	-0.6057	0.273484
46	-0.133569	-1.0346	0.152499
47	-0.119485	-0.9255	0.179199
48	0.0116	0.0899	0.464352
49	-0.113303	-0.8776	0.191819
50	-0.108478	-0.8403	0.202047
51	-0.053758	-0.4164	0.339299
52	-0.0373	-0.2889	0.386818
53	-0.033159	-0.2568	0.399087
54	0.004618	0.0358	0.485793
55	-0.024197	-0.1874	0.425979
56	-0.038149	-0.2955	0.384315
57	0.014153	0.1096	0.456536
58	-0.004826	-0.0374	0.485153
59	-0.004886	-0.0378	0.484967
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.142074	1.1005	0.137755
2	-0.029685	-0.2299	0.40946
3	0.258928	2.0056	0.024705
4	-0.132526	-1.0265	0.154378
5	0.167055	1.294	0.100312
6	0.563568	4.3654	2.5e-05
7	-0.155293	-1.2029	0.116871
8	-0.219418	-1.6996	0.047192
9	0.03137	0.243	0.404421
10	-0.077324	-0.599	0.27573
11	-0.01574	-0.1219	0.451684
12	0.431306	3.3409	0.00072
13	-0.116004	-0.8986	0.186239
14	-0.048852	-0.3784	0.353233
15	-0.137256	-1.0632	0.14598
16	-0.003832	-0.0297	0.48821
17	-0.080634	-0.6246	0.267304
18	-0.149469	-1.1578	0.12577
19	0.063971	0.4955	0.311023
20	0.113279	0.8775	0.19187
21	-0.123405	-0.9559	0.171482
22	0.034299	0.2657	0.395699
23	0.035223	0.2728	0.392957
24	0.009331	0.0723	0.471311
25	-0.089256	-0.6914	0.245998
26	0.035051	0.2715	0.393468
27	-0.017318	-0.1341	0.446869
28	-0.050839	-0.3938	0.347565
29	-0.067315	-0.5214	0.301997
30	-0.037832	-0.293	0.385249
31	0.043917	0.3402	0.367454
32	-0.111884	-0.8666	0.194794
33	-0.04354	-0.3373	0.368549
34	0.108561	0.8409	0.201868
35	-0.059497	-0.4609	0.323281
36	0.003363	0.0261	0.489651
37	-0.031543	-0.2443	0.403904
38	-0.038597	-0.299	0.382998
39	0.06928	0.5366	0.296751
40	-0.069918	-0.5416	0.295056
41	-0.029147	-0.2258	0.411072
42	-0.226589	-1.7552	0.042169
43	-0.006005	-0.0465	0.481528
44	0.06295	0.4876	0.313803
45	-0.008758	-0.0678	0.473071
46	-0.028797	-0.2231	0.412123
47	0.014301	0.1108	0.456084
48	-0.100952	-0.782	0.218653
49	0.015518	0.1202	0.452362
50	0.010931	0.0847	0.466401
51	-0.02318	-0.1796	0.429054
52	0.087412	0.6771	0.250475
53	0.09254	0.7168	0.238135
54	0.104448	0.8091	0.210841
55	-0.012404	-0.0961	0.461888
56	-0.005338	-0.0413	0.483578
57	0.074911	0.5803	0.281957
58	-0.096932	-0.7508	0.227845
59	-0.036321	-0.2813	0.389709
60	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229702387l64haboygn6zc8n/1qm1k1229702284.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229702387l64haboygn6zc8n/1qm1k1229702284.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229702387l64haboygn6zc8n/26s2r1229702284.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229702387l64haboygn6zc8n/26s2r1229702284.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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