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opdracht 6 bis eigen reeks

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Mon, 15 Nov 2010 14:56:33 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/15/t1289832975wqg0wgbxjv5plkj.htm/, Retrieved Mon, 15 Nov 2010 15:56:17 +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/2010/Nov/15/t1289832975wqg0wgbxjv5plkj.htm/},
    year = {2010},
}
@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 = {2010},
    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:

KDGP2W12

Dataseries X:

» Textbox « » Textfile « » CSV «

78,1 66,7 79 65,2 66,5 77,2 80,2 77,9 78 86,8 92,9 185,8 91 79,1 84,2 70,1 71,3 79,6 92,3 78,7 82,5 98,2 115,4 205,6 94 83,2 80,3 70,4 71,1 78,8 86,3 77,5 80,1 89,8 99,9 218 85,4 77,5 78,6 68,8 64,8 79,8 94,3 79,9 87,5 99,1 109,9 273,6 91,3 80,6 80,4 71,8 75,5 86,6 91,5 86,8 84,6 88,6 102,1 260,3 79 70,6 79,3 66,8 61,2 72,5 83,5 75,8 83,4 89,4 104,9 251,6 80 76,3 81,1 63,1 63,5 78,8 91,7 83,8 83,8 95,8 108,9 258,2 88,7 79,5 74,3 70,5 59,1 73,2 81,2 75 74,6 89,5 107 246,4 83,6 72,1 68,7 60,1 61,1 72,7 85,3 71,4 75,2 89,8 100,9 222,7

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.132389	1.3758	0.085861
2	-0.020452	-0.2125	0.416043
3	-0.091719	-0.9532	0.171316
4	-0.171307	-1.7803	0.038921
5	-0.153163	-1.5917	0.057186
6	-0.159647	-1.6591	0.049998
7	-0.168103	-1.747	0.041742
8	-0.190346	-1.9781	0.02523
9	-0.109638	-1.1394	0.12853
10	-0.052104	-0.5415	0.294644
11	0.097712	1.0155	0.156079
12	0.900764	9.361	0
13	0.104558	1.0866	0.139816
14	-0.029995	-0.3117	0.377926
15	-0.09292	-0.9657	0.168187
16	-0.160876	-1.6719	0.048722
17	-0.146921	-1.5268	0.064861
18	-0.152906	-1.589	0.057487
19	-0.161322	-1.6765	0.048266
20	-0.176755	-1.8369	0.034488
21	-0.099689	-1.036	0.151258
22	-0.053244	-0.5533	0.290591
23	0.081135	0.8432	0.200496
24	0.796669	8.2792	0
25	0.095993	0.9976	0.160354
26	-0.017336	-0.1802	0.428682
27	-0.072269	-0.751	0.227131
28	-0.130388	-1.355	0.089118
29	-0.114962	-1.1947	0.117406
30	-0.12095	-1.2569	0.105742
31	-0.128542	-1.3359	0.092203
32	-0.148046	-1.5385	0.063421
33	-0.077453	-0.8049	0.211318
34	-0.045188	-0.4696	0.319791
35	0.070728	0.735	0.231958
36	0.676939	7.035	0
37	0.080154	0.833	0.203346
38	-0.017758	-0.1845	0.426966
39	-0.068216	-0.7089	0.239951
40	-0.116445	-1.2101	0.114435
41	-0.103603	-1.0767	0.142012
42	-0.111027	-1.1538	0.12556
43	-0.122005	-1.2679	0.103777
44	-0.137093	-1.4247	0.078561
45	-0.079369	-0.8248	0.205644
46	-0.053688	-0.5579	0.28902
47	0.049875	0.5183	0.302648
48	0.531833	5.527	0

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.132389	1.3758	0.085861
2	-0.038656	-0.4017	0.34434
3	-0.085411	-0.8876	0.188358
4	-0.152222	-1.5819	0.058294
5	-0.122382	-1.2718	0.103082
6	-0.153171	-1.5918	0.057176
7	-0.188568	-1.9597	0.026306
8	-0.256059	-2.661	0.004489
9	-0.229231	-2.3822	0.009478
10	-0.266712	-2.7717	0.003284
11	-0.192085	-1.9962	0.024214
12	0.860808	8.9458	0
13	-0.315676	-3.2806	0.000698
14	-0.155262	-1.6135	0.054774
15	-0.058352	-0.6064	0.272758
16	-0.047606	-0.4947	0.310896
17	-0.090686	-0.9424	0.174037
18	-0.014141	-0.147	0.441719
19	0.031529	0.3277	0.3719
20	0.048102	0.4999	0.309086
21	-0.010693	-0.1111	0.455861
22	0.010866	0.1129	0.45515
23	-0.057927	-0.602	0.274219
24	-0.203294	-2.1127	0.018466
25	0.076637	0.7964	0.213763
26	0.062454	0.649	0.258845
27	0.019607	0.2038	0.419461
28	0.032051	0.3331	0.369859
29	0.097471	1.0129	0.156675
30	0.048287	0.5018	0.308411
31	0.030724	0.3193	0.375062
32	-0.016433	-0.1708	0.43236
33	0.033344	0.3465	0.364814
34	0.011591	0.1205	0.452171
35	0.039517	0.4107	0.341064
36	-0.107778	-1.1201	0.132586
37	0.061085	0.6348	0.263445
38	0.017153	0.1783	0.429426
39	-0.0067	-0.0696	0.472309
40	0.002215	0.023	0.490837
41	-0.022998	-0.239	0.405778
42	-0.049587	-0.5153	0.30369
43	-0.080362	-0.8351	0.20274
44	-0.003133	-0.0326	0.487043
45	-0.07706	-0.8008	0.212493
46	-0.056169	-0.5837	0.280311
47	-0.022211	-0.2308	0.408943
48	-0.189927	-1.9738	0.02548

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/15/t1289832975wqg0wgbxjv5plkj/1zrlv1289832991.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t1289832975wqg0wgbxjv5plkj/1zrlv1289832991.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t1289832975wqg0wgbxjv5plkj/2zrlv1289832991.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/15/t1289832975wqg0wgbxjv5plkj/2zrlv1289832991.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; 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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