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Autocorrelatiefunctie met differntiatie (Verkoopprijzen)

*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: Thu, 31 Dec 2009 03:14:57 -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/Dec/31/t1262254611a0j37cait378411.htm/, Retrieved Thu, 31 Dec 2009 11:16:54 +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/Dec/31/t1262254611a0j37cait378411.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 «

2072.65 2020.13 2032.76 2050.31 2128.98 2122.14 2122.89 2091.95 2002.97 1923.21 1834.44 1819.15 1792.00 1822.40 1900.70 1903.00 1958.80 1820.50 1719.80 1661.10 1664.40 1703.40 1774.90 1795.00 1816.30 1867.40 1900.00 1961.10 2065.70 2073.50 2080.80 2118.00 2099.00 2085.20 1937.70 1749.50 1750.30 1675.60 1697.50 1699.80 1655.90 1636.00 1614.20 1602.30 1548.70 1556.10 1526.90 1509.20 1566.30 1596.00 1654.50 1664.20 1687.70 1691.00 1664.60 1697.50 1685.10 1643.00 1559.60 1560.20 1590.16 1604.93 1661.80 1670.73 1692.40 1688.17 1658.04 1613.46 1595.11 1558.83 1526.65 1475.19

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	-0.352408	-2.9485	0.002169
2	0.098816	0.8268	0.205592
3	-0.041885	-0.3504	0.363531
4	-0.302627	-2.532	0.006795
5	0.156753	1.3115	0.096988
6	-0.146897	-1.229	0.111588
7	0.162219	1.3572	0.089535
8	-0.167455	-1.401	0.082812
9	0.137921	1.1539	0.126227
10	-0.029535	-0.2471	0.402773
11	-0.023582	-0.1973	0.422081
12	0.253097	2.1176	0.018883
13	-0.338176	-2.8294	0.00304
14	0.169606	1.419	0.080165
15	-0.171649	-1.4361	0.077712
16	-0.029978	-0.2508	0.401347
17	0.253639	2.1221	0.018685
18	-0.039446	-0.33	0.371183
19	-0.094981	-0.7947	0.214746
20	0.05331	0.446	0.328477
21	-0.158605	-1.327	0.094413
22	0.018272	0.1529	0.439467
23	0.133465	1.1166	0.133982
24	0.010551	0.0883	0.464953
25	-0.005136	-0.043	0.482922
26	-0.014303	-0.1197	0.452546
27	0.055709	0.4661	0.321298
28	-0.066139	-0.5534	0.29089
29	0.100818	0.8435	0.20091
30	-0.101821	-0.8519	0.198589
31	-0.147941	-1.2378	0.10997
32	0.163547	1.3683	0.087792
33	-0.219115	-1.8332	0.035509
34	0.231419	1.9362	0.028442
35	-0.044451	-0.3719	0.355544
36	0.000134	0.0011	0.499553
37	0.057246	0.479	0.316732
38	-0.111364	-0.9317	0.177337
39	0.118924	0.995	0.161585
40	-0.043928	-0.3675	0.357166
41	0.101838	0.852	0.19855
42	-0.090739	-0.7592	0.225147
43	-0.027649	-0.2313	0.408868
44	0.005888	0.0493	0.480424
45	-0.106266	-0.8891	0.188501
46	0.141597	1.1847	0.120074
47	-0.102845	-0.8605	0.196236
48	0.112104	0.9379	0.175752
49	0.015513	0.1298	0.44855
50	-0.021508	-0.1799	0.428858
51	-0.009452	-0.0791	0.468598
52	-0.035445	-0.2966	0.383844
53	0.003945	0.033	0.486882
54	-0.031952	-0.2673	0.395002
55	-0.00237	-0.0198	0.492119
56	0.005343	0.0447	0.482236
57	0.016915	0.1415	0.443932
58	0.023783	0.199	0.421428
59	-0.008281	-0.0693	0.472481
60	0.005156	0.0431	0.482858

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.352408	-2.9485	0.002169
2	-0.028973	-0.2424	0.404587
3	-0.018585	-0.1555	0.43844
4	-0.366791	-3.0688	0.001528
5	-0.094462	-0.7903	0.216002
6	-0.136905	-1.1454	0.127966
7	0.020326	0.1701	0.432728
8	-0.27167	-2.273	0.013051
9	-0.011487	-0.0961	0.461855
10	-0.056418	-0.472	0.319188
11	-0.0364	-0.3045	0.380809
12	0.162289	1.3578	0.089443
13	-0.172109	-1.44	0.077167
14	-0.056157	-0.4698	0.319964
15	-0.103861	-0.869	0.193918
16	-0.100294	-0.8391	0.202129
17	0.119906	1.0032	0.159608
18	0.162185	1.3569	0.089581
19	-0.291966	-2.4428	0.008551
20	0.050656	0.4238	0.336499
21	-0.174449	-1.4595	0.074445
22	-0.047638	-0.3986	0.345712
23	0.016411	0.1373	0.445592
24	0.053251	0.4455	0.328655
25	0.001993	0.0167	0.493371
26	-0.066768	-0.5586	0.289101
27	0.141728	1.1858	0.119859
28	0.038257	0.3201	0.374931
29	-0.010028	-0.0839	0.466686
30	0.006942	0.0581	0.476926
31	-0.107392	-0.8985	0.185997
32	0.035512	0.2971	0.383628
33	-0.023114	-0.1934	0.423608
34	-0.146565	-1.2262	0.112107
35	-0.088001	-0.7363	0.232013
36	0.017759	0.1486	0.441156
37	-0.044134	-0.3693	0.356527
38	0.000678	0.0057	0.497744
39	0.050574	0.4231	0.336749
40	0.060715	0.508	0.306534
41	0.025008	0.2092	0.417437
42	0.119043	0.996	0.161344
43	0.062749	0.525	0.300624
44	-0.094654	-0.7919	0.215538
45	0.024257	0.2029	0.419882
46	-0.041644	-0.3484	0.364286
47	-0.064991	-0.5438	0.294169
48	0.14323	1.1983	0.117412
49	0.03653	0.3056	0.380395
50	-0.031155	-0.2607	0.397558
51	-0.052468	-0.439	0.331013
52	-0.070456	-0.5895	0.278721
53	0.037909	0.3172	0.376029
54	0.057567	0.4816	0.315783
55	-0.023863	-0.1996	0.421167
56	-0.011318	-0.0947	0.462414
57	0.01146	0.0959	0.461943
58	0.066836	0.5592	0.288909
59	-0.087336	-0.7307	0.233698
60	0.002561	0.0214	0.491481

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/31/t1262254611a0j37cait378411/1y6g01262254494.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/31/t1262254611a0j37cait378411/1y6g01262254494.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/31/t1262254611a0j37cait378411/235kz1262254494.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/31/t1262254611a0j37cait378411/235kz1262254494.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = -1.7 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = -1.7 ; par3 = 2 ; par4 = 0 ; 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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