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paper: (p)acf 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 09:01:23 -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/t12297025558jk58zyoboduppc.htm/, Retrieved Fri, 19 Dec 2008 17:02:35 +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/t12297025558jk58zyoboduppc.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 83.8 109.5 102.3 102.5 116.4 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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.200387	1.5522	0.062938
2	0.038384	0.2973	0.383623
3	0.281082	2.1772	0.016703
4	0.007143	0.0553	0.478031
5	0.132997	1.0302	0.153528
6	0.517398	4.0077	8.6e-05
7	0.07922	0.6136	0.270887
8	-0.09948	-0.7706	0.221993
9	0.182029	1.41	0.081852
10	-0.073913	-0.5725	0.284552
11	0.044503	0.3447	0.365756
12	0.642196	4.9744	3e-06
13	0.023376	0.1811	0.428462
14	-0.081264	-0.6295	0.265716
15	0.126084	0.9766	0.166334
16	-0.10733	-0.8314	0.204528
17	-0.010374	-0.0804	0.46811
18	0.273988	2.1223	0.018975
19	-0.04367	-0.3383	0.36817
20	-0.153522	-1.1892	0.119527
21	0.024843	0.1924	0.424025
22	-0.173151	-1.3412	0.092452
23	-0.06724	-0.5208	0.302199
24	0.34717	2.6892	0.00463
25	-0.103472	-0.8015	0.213005
26	-0.136992	-1.0611	0.14644
27	-0.00613	-0.0475	0.481144
28	-0.1887	-1.4617	0.074525
29	-0.105215	-0.815	0.209149
30	0.103729	0.8035	0.212434
31	-0.128231	-0.9933	0.162283
32	-0.196046	-1.5186	0.067062
33	-0.072939	-0.565	0.287096
34	-0.200822	-1.5556	0.062536
35	-0.123499	-0.9566	0.171298
36	0.169215	1.3107	0.097471
37	-0.140433	-1.0878	0.14052
38	-0.153983	-1.1927	0.118831
39	-0.050192	-0.3888	0.349407
40	-0.141779	-1.0982	0.13825
41	-0.093532	-0.7245	0.235788
42	0.021864	0.1694	0.433043
43	-0.130943	-1.0143	0.15726
44	-0.181877	-1.4088	0.082026
45	-0.080702	-0.6251	0.267133
46	-0.14039	-1.0875	0.140593
47	-0.125029	-0.9685	0.168348
48	0.013679	0.106	0.457985
49	-0.118497	-0.9179	0.181179
50	-0.113314	-0.8777	0.191797
51	-0.056869	-0.4405	0.330578
52	-0.039711	-0.3076	0.379725
53	-0.03491	-0.2704	0.393887
54	0.00542	0.042	0.483326
55	-0.025123	-0.1946	0.423181
56	-0.0398	-0.3083	0.379466
57	0.015261	0.1182	0.453148
58	-0.005738	-0.0444	0.482347
59	-0.005155	-0.0399	0.484141
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.200387	1.5522	0.062938
2	-0.001845	-0.0143	0.494324
3	0.285198	2.2091	0.015497
4	-0.118303	-0.9164	0.181571
5	0.186031	1.441	0.077393
6	0.432154	3.3475	0.000706
7	-0.095658	-0.741	0.230803
8	-0.196167	-1.5195	0.066945
9	0.052086	0.4035	0.344024
10	-0.101664	-0.7875	0.21705
11	0.05298	0.4104	0.341494
12	0.554547	4.2955	3.2e-05
13	-0.246682	-1.9108	0.030406
14	-0.02399	-0.1858	0.426605
15	-0.166381	-1.2888	0.10121
16	-0.067529	-0.5231	0.301422
17	-0.087548	-0.6781	0.250143
18	-0.221786	-1.7179	0.045482
19	0.128351	0.9942	0.162059
20	0.133287	1.0324	0.153006
21	-0.130523	-1.011	0.158032
22	0.070419	0.5455	0.293729
23	-0.021396	-0.1657	0.434463
24	-0.051311	-0.3975	0.346221
25	-0.073725	-0.5711	0.285042
26	-0.059501	-0.4609	0.323271
27	0.0112	0.0868	0.465578
28	-0.034016	-0.2635	0.396539
29	-0.084126	-0.6516	0.258561
30	0.067233	0.5208	0.302217
31	-0.050346	-0.39	0.348966
32	-0.082753	-0.641	0.26198
33	0.024233	0.1877	0.425869
34	0.034159	0.2646	0.396113
35	-0.047368	-0.3669	0.357488
36	-0.019067	-0.1477	0.441542
37	0.013474	0.1044	0.458613
38	-0.021474	-0.1663	0.434226
39	-0.031868	-0.2468	0.402935
40	0.072752	0.5635	0.287586
41	0.032865	0.2546	0.399963
42	-0.114854	-0.8897	0.188602
43	-0.06572	-0.5091	0.306287
44	-0.006995	-0.0542	0.478485
45	-0.004351	-0.0337	0.486613
46	-0.050584	-0.3918	0.348288
47	-0.045232	-0.3504	0.363646
48	-0.102692	-0.7954	0.214745
49	0.101132	0.7834	0.218248
50	0.000122	9e-04	0.499624
51	-0.015845	-0.1227	0.451363
52	0.12291	0.9521	0.172443
53	-0.00887	-0.0687	0.472727
54	0.027645	0.2141	0.415584
55	0.059463	0.4606	0.323375
56	0.011349	0.0879	0.465122
57	0.077883	0.6033	0.274298
58	-0.114239	-0.8849	0.189874
59	0.050001	0.3873	0.349949
60	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t12297025558jk58zyoboduppc/1vlra1229702478.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t12297025558jk58zyoboduppc/1vlra1229702478.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t12297025558jk58zyoboduppc/2l5121229702478.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t12297025558jk58zyoboduppc/2l5121229702478.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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