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autocorrelatie goudkoers

*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: Sun, 19 Dec 2010 13:20:23 +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/Dec/19/t129276497717806xikkzmwlga.htm/, Retrieved Sun, 19 Dec 2010 14:23:00 +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/Dec/19/t129276497717806xikkzmwlga.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

10570 10297 10635 10872 10296 10383 10431 10574 10653 10805 10872 10625 10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032 17696 17745 19394 20148 20108 18584 18441 18391 19178 18079 18483 19644 19195 19650 20830 23595 22937 21814 21928 21777 21383 21467 22052 22680 24320 24977 25204

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.943798	8.0638	0
2	0.884449	7.5567	0
3	0.832321	7.1114	0
4	0.789079	6.7419	0
5	0.74362	6.3535	0
6	0.70648	6.0362	0
7	0.674309	5.7613	0
8	0.638791	5.4578	0
9	0.602745	5.1499	1e-06
10	0.564692	4.8247	4e-06
11	0.518859	4.4331	1.6e-05
12	0.461781	3.9455	9.1e-05
13	0.417821	3.5699	0.000318
14	0.377142	3.2223	0.000951
15	0.339463	2.9004	0.002461
16	0.29941	2.5582	0.006299
17	0.267007	2.2813	0.012724
18	0.240314	2.0532	0.021816
19	0.206357	1.7631	0.041033
20	0.182002	1.555	0.062133
21	0.156989	1.3413	0.091988
22	0.131163	1.1207	0.133054
23	0.090488	0.7731	0.220972
24	0.050365	0.4303	0.334115
25	0.014723	0.1258	0.450121
26	-0.010645	-0.091	0.463889
27	-0.038756	-0.3311	0.370748
28	-0.059469	-0.5081	0.306457
29	-0.069304	-0.5921	0.277795
30	-0.081435	-0.6958	0.244387
31	-0.088949	-0.76	0.224857
32	-0.099782	-0.8525	0.198352
33	-0.112347	-0.9599	0.170139
34	-0.131513	-1.1236	0.132423
35	-0.150784	-1.2883	0.100856
36	-0.173069	-1.4787	0.071761
37	-0.190252	-1.6255	0.054182
38	-0.205368	-1.7547	0.041756
39	-0.22428	-1.9163	0.029624
40	-0.237591	-2.03	0.023002
41	-0.255296	-2.1813	0.016193
42	-0.278031	-2.3755	0.010076
43	-0.303	-2.5888	0.005808
44	-0.323453	-2.7636	0.003616
45	-0.355512	-3.0375	0.001654
46	-0.378534	-3.2342	0.000917
47	-0.39274	-3.3556	0.00063
48	-0.409724	-3.5007	0.000398
49	-0.418297	-3.5739	0.000314
50	-0.418988	-3.5798	0.000308
51	-0.415236	-3.5478	0.000342
52	-0.41653	-3.5588	0.00033
53	-0.415175	-3.5473	0.000342
54	-0.41069	-3.5089	0.000387
55	-0.403788	-3.45	0.000468
56	-0.401738	-3.4324	0.000494
57	-0.392951	-3.3574	0.000626
58	-0.378113	-3.2306	0.000927
59	-0.365047	-3.119	0.001299
60	-0.34999	-2.9903	0.001899

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.943798	8.0638	0
2	-0.057716	-0.4931	0.311703
3	0.035585	0.304	0.380981
4	0.049365	0.4218	0.337215
5	-0.045565	-0.3893	0.34909
6	0.061301	0.5238	0.301018
7	0.022131	0.1891	0.425275
8	-0.047552	-0.4063	0.34286
9	-0.006696	-0.0572	0.477266
10	-0.041428	-0.354	0.362193
11	-0.095453	-0.8156	0.208705
12	-0.123711	-1.057	0.147001
13	0.077913	0.6657	0.253853
14	-0.031469	-0.2689	0.394393
15	-0.003689	-0.0315	0.48747
16	-0.039684	-0.3391	0.36777
17	0.023167	0.1979	0.421823
18	0.036398	0.311	0.378348
19	-0.077147	-0.6591	0.255939
20	0.086746	0.7412	0.230488
21	-0.030851	-0.2636	0.39642
22	-0.016229	-0.1387	0.445049
23	-0.143374	-1.225	0.112259
24	-0.057805	-0.4939	0.311434
25	0.00693	0.0592	0.476473
26	0.046776	0.3997	0.345289
27	-0.058468	-0.4995	0.309448
28	0.019908	0.1701	0.432703
29	0.08435	0.7207	0.236702
30	-0.031927	-0.2728	0.392894
31	0.038127	0.3258	0.372771
32	-0.015317	-0.1309	0.44812
33	-0.016485	-0.1409	0.444187
34	-0.024686	-0.2109	0.416769
35	-0.075213	-0.6426	0.261241
36	-0.081416	-0.6956	0.244439
37	0.015477	0.1322	0.44758
38	-0.016828	-0.1438	0.443037
39	-0.108389	-0.9261	0.178729
40	0.018477	0.1579	0.4375
41	-0.052244	-0.4464	0.328326
42	-0.090274	-0.7713	0.221508
43	-0.021218	-0.1813	0.428323
44	-0.013147	-0.1123	0.455436
45	-0.097633	-0.8342	0.203452
46	0.055668	0.4756	0.317879
47	0.014062	0.1201	0.452347
48	-0.105804	-0.904	0.184487
49	0.099322	0.8486	0.199437
50	0.041229	0.3523	0.36283
51	-0.032546	-0.2781	0.390873
52	-0.010684	-0.0913	0.46376
53	0.017036	0.1456	0.442336
54	0.013474	0.1151	0.454334
55	-0.002	-0.0171	0.493206
56	-0.015679	-0.134	0.446901
57	0.02032	0.1736	0.431325
58	0.048242	0.4122	0.340708
59	-0.030487	-0.2605	0.397612
60	-0.023878	-0.204	0.419454

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/149pd1292764821.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/149pd1292764821.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/2xi7y1292764821.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/2xi7y1292764821.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/3xi7y1292764821.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t129276497717806xikkzmwlga/3xi7y1292764821.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; 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 (par8 != '') par8 <- as.numeric(par8)

ox <- x

if (par8 == '') {

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

} else {

x <- log(x,base=par8)

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='picts.png')

op <- par(mfrow=c(2,1))

plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')

if (par8=='') {

mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

} else {

mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

}

plot(x,type='l', main=mytitle,xlab='time',ylab='value')

par(op)

dev.off()

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)

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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