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Correlation Function na differentiatie

*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: Sat, 18 Dec 2010 13:07:11 +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/18/t12926776731fm94azc6l9l6jh.htm/, Retrieved Sat, 18 Dec 2010 14:07:53 +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/18/t12926776731fm94azc6l9l6jh.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 «

1038.00 934.00 988.00 870.00 854.00 834.00 872.00 954.00 870.00 1238.00 1082.00 1053.00 934.00 787.00 1081.00 908.00 995.00 825.00 822.00 856.00 887.00 1094.00 990.00 936.00 1097.00 918.00 926.00 907.00 899.00 971.00 1087.00 1000.00 1071.00 1190.00 1116.00 1070.00 1314.00 1068.00 1185.00 1215.00 1145.00 1251.00 1363.00 1368.00 1535.00 1853.00 1866.00 2023.00 1373.00 1968.00 1424.00 1160.00 1243.00 1375.00 1539.00 1773.00 1906.00 2076.00 2004.00

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.524067	-3.5544	0.000445
2	0.148266	1.0056	0.159937
3	0.020886	0.1417	0.443984
4	-0.108519	-0.736	0.232729
5	-0.061546	-0.4174	0.339155
6	0.069291	0.47	0.320304
7	-0.076813	-0.521	0.302442
8	0.039916	0.2707	0.393908
9	0.023038	0.1562	0.43826
10	0.025898	0.1756	0.43067
11	0.055528	0.3766	0.354099
12	-0.130776	-0.887	0.189855
13	0.017695	0.12	0.452497
14	-0.004464	-0.0303	0.487989
15	0.039212	0.266	0.395733
16	-0.008162	-0.0554	0.478048
17	0.062212	0.4219	0.337517
18	-0.05875	-0.3985	0.346067
19	-0.045023	-0.3054	0.380735
20	0.104697	0.7101	0.240617
21	-0.16977	-1.1514	0.127751
22	0.14552	0.987	0.164412
23	-0.073073	-0.4956	0.311266
24	-0.061007	-0.4138	0.340483
25	0.16795	1.1391	0.130281
26	-0.107645	-0.7301	0.234521
27	0.035992	0.2441	0.404117
28	-0.106021	-0.7191	0.237867
29	0.063248	0.429	0.334974
30	-0.012949	-0.0878	0.465198
31	0.084268	0.5715	0.285211
32	-0.053009	-0.3595	0.360424
33	0.094211	0.639	0.263006
34	-0.129834	-0.8806	0.191563
35	0.092575	0.6279	0.266596
36	-0.060772	-0.4122	0.341063
37	-0.023001	-0.156	0.438359
38	0.006563	0.0445	0.482343
39	0.012842	0.0871	0.465486
40	0.007614	0.0516	0.479521
41	0.019075	0.1294	0.448814
42	-0.007237	-0.0491	0.480534
43	-0.010575	-0.0717	0.471567
44	-0.005092	-0.0345	0.4863
45	0.001608	0.0109	0.495672
46	NA	NA	NA
47	NA	NA	NA
48	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.524067	-3.5544	0.000445
2	-0.174233	-1.1817	0.121698
3	0.029596	0.2007	0.420898
4	-0.081301	-0.5514	0.292012
5	-0.23439	-1.5897	0.059375
6	-0.115992	-0.7867	0.217746
7	-0.093934	-0.6371	0.263612
8	-0.068375	-0.4637	0.32251
9	-0.03814	-0.2587	0.398519
10	0.025055	0.1699	0.432904
11	0.118244	0.802	0.213347
12	-0.089358	-0.6061	0.273728
13	-0.161236	-1.0936	0.139922
14	-0.078957	-0.5355	0.297437
15	0.091015	0.6173	0.270043
16	0.072041	0.4886	0.313722
17	0.052424	0.3556	0.3619
18	-0.019958	-0.1354	0.446458
19	-0.137768	-0.9344	0.177491
20	0.027401	0.1858	0.426693
21	-0.094515	-0.641	0.26234
22	0.058582	0.3973	0.346483
23	0.041617	0.2823	0.389506
24	-0.162196	-1.1001	0.138514
25	-0.0102	-0.0692	0.472572
26	-0.036355	-0.2466	0.403169
27	0.026839	0.182	0.42818
28	-0.190778	-1.2939	0.101076
29	-0.091455	-0.6203	0.269067
30	0.016151	0.1095	0.456625
31	0.093772	0.636	0.263968
32	0.009074	0.0615	0.475596
33	0.028586	0.1939	0.423563
34	-0.032913	-0.2232	0.412173
35	0.010518	0.0713	0.471719
36	-0.015629	-0.106	0.45802
37	-0.029056	-0.1971	0.422323
38	0.030827	0.2091	0.417655
39	0.030099	0.2041	0.419571
40	-0.074151	-0.5029	0.308712
41	-0.053422	-0.3623	0.359384
42	-0.066397	-0.4503	0.327295
43	0.043367	0.2941	0.384992
44	0.03159	0.2143	0.415648
45	-0.014907	-0.1011	0.459954
46	NA	NA	NA
47	NA	NA	NA
48	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t12926776731fm94azc6l9l6jh/15ae51292677628.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t12926776731fm94azc6l9l6jh/15ae51292677628.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t12926776731fm94azc6l9l6jh/2ykdq1292677628.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t12926776731fm94azc6l9l6jh/2ykdq1292677628.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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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