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autocorrelatie non seasonal differencing consumptieprijsindex

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Mon, 03 May 2010 13:21:05 +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/May/03/t1272893018iong1ozxt4sckay.htm/, Retrieved Mon, 03 May 2010 15:23:38 +0200

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/May/03/t1272893018iong1ozxt4sckay.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:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

2 2.4 1.5 1.2 1.5 0.6 2.7 3.7 4.9 6.6 7.4 7.2 5.3 4.7 6.1 6.6 7 7.5 6.6 7.8 4.7 5.4 4.3 4.5 5.8 4.6 5.2 3.6 4.8 6.7 6.3 4.8 8.7 6.8 7.4 9 7.9 9.1 8.7 9.8 6.4 6.1 4.7 4.8 4.2 2.8 6.1 5.8 4.9 4.6 4.1 3.6 5.9 4.5 4.8 5.7 5 7 4.6 2.6 5 4.1 3.2 0 2.3 3.8 4.5 5.9 5 4.2 4.5 6

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	-0.267549	-2.2544	0.013629
2	-0.010398	-0.0876	0.465216
3	0.028402	0.2393	0.405773
4	-0.142262	-1.1987	0.117311
5	0.12648	1.0657	0.145075
6	-0.141549	-1.1927	0.118476
7	0.034518	0.2909	0.386005
8	-0.044033	-0.371	0.355862
9	0.072677	0.6124	0.271119
10	-0.035814	-0.3018	0.381854
11	0.085661	0.7218	0.236397
12	-0.29789	-2.5101	0.007176
13	0.031511	0.2655	0.39569
14	0.066315	0.5588	0.289036
15	0.039435	0.3323	0.370326
16	-0.114012	-0.9607	0.169987
17	-0.103242	-0.8699	0.193635
18	0.256424	2.1607	0.017048
19	-0.109821	-0.9254	0.178955
20	0.166121	1.3998	0.08297
21	-0.071379	-0.6014	0.274728
22	0.06767	0.5702	0.285171
23	0.135197	1.1392	0.129226
24	-0.201101	-1.6945	0.047276
25	0.118556	0.999	0.160601
26	-0.110758	-0.9333	0.176924
27	-0.113699	-0.958	0.170645
28	0.196385	1.6548	0.051193
29	-0.004679	-0.0394	0.48433
30	-0.07496	-0.6316	0.26483
31	-0.03375	-0.2844	0.388473
32	0.02489	0.2097	0.417241
33	0.013778	0.1161	0.453951
34	-0.185213	-1.5606	0.061528
35	-0.038372	-0.3233	0.373698
36	0.108783	0.9166	0.181221
37	-0.039039	-0.3289	0.371581
38	0.122396	1.0313	0.152945
39	-0.009769	-0.0823	0.467314
40	-0.055985	-0.4717	0.31928
41	0.055996	0.4718	0.319246
42	-0.027944	-0.2355	0.407264
43	0.102862	0.8667	0.194504
44	-0.132734	-1.1184	0.133575
45	-0.017095	-0.144	0.442938
46	0.065363	0.5508	0.291765
47	-0.032843	-0.2767	0.39139
48	0.01893	0.1595	0.436861

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.267549	-2.2544	0.013629
2	-0.088301	-0.744	0.229656
3	0.0019	0.016	0.493637
4	-0.145901	-1.2294	0.111493
5	0.053817	0.4535	0.325798
6	-0.117606	-0.991	0.162534
7	-0.026011	-0.2192	0.413572
8	-0.083575	-0.7042	0.241802
9	0.069532	0.5859	0.279905
10	-0.051068	-0.4303	0.334137
11	0.106675	0.8989	0.185882
12	-0.331424	-2.7926	0.003357
13	-0.090614	-0.7635	0.22384
14	-0.051524	-0.4341	0.332749
15	0.13711	1.1553	0.125919
16	-0.258615	-2.1791	0.016321
17	-0.123939	-1.0443	0.149938
18	0.09749	0.8215	0.207066
19	0.026602	0.2242	0.411642
20	0.068997	0.5814	0.281414
21	0.035584	0.2998	0.382588
22	0.115893	0.9765	0.166059
23	0.212195	1.788	0.039022
24	-0.20124	-1.6957	0.047164
25	0.017369	0.1464	0.442029
26	-0.002492	-0.021	0.491653
27	-0.08404	-0.7081	0.24059
28	0.004999	0.0421	0.483261
29	-0.000347	-0.0029	0.498837
30	0.049005	0.4129	0.340453
31	-0.072429	-0.6103	0.271806
32	0.061878	0.5214	0.301857
33	-0.017259	-0.1454	0.442394
34	-0.146012	-1.2303	0.11132
35	-0.034399	-0.2899	0.386386
36	-0.002098	-0.0177	0.492971
37	-0.04456	-0.3755	0.354215
38	0.071579	0.6031	0.274169
39	-0.005126	-0.0432	0.482834
40	-0.076528	-0.6448	0.260555
41	-0.035169	-0.2963	0.383919
42	0.051806	0.4365	0.33189
43	-0.05889	-0.4962	0.310637
44	-0.04728	-0.3984	0.345769
45	-0.016184	-0.1364	0.445959
46	-0.09847	-0.8297	0.204738
47	-0.065619	-0.5529	0.291028
48	-0.031784	-0.2678	0.394809

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/03/t1272893018iong1ozxt4sckay/1x6it1272892862.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/03/t1272893018iong1ozxt4sckay/1x6it1272892862.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/03/t1272893018iong1ozxt4sckay/2x6it1272892862.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/03/t1272893018iong1ozxt4sckay/2x6it1272892862.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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