Home » date » 2010 » Dec » 18 »

Gedifferentieerde ACF paper uitvoer Belgie

*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 15:14:54 +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/t1292685195r9sl9oqmsyokus7.htm/, Retrieved Sat, 18 Dec 2010 16:13:18 +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/t1292685195r9sl9oqmsyokus7.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 «

14544 15116 17413 16181 15607 17160 14915 13768 17487 16198 17535 16571 16198 16554 19554 15903 18003 18329 16260 14851 18174 18406 18466 16016 17428 17167 19630 17183 18344 19301 18147 16192 18374 20515 18957 16471 18746 19009 19211 20547 19325 20605 20056 16141 20359 19711 15638 14384 13855 14308 15290 14423 13779 15686 14733 12522 16189 16059 16007 15806 15160

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	-0.418123	-2.8968	0.002831
2	0.04474	0.31	0.378964
3	0.38937	2.6976	0.004804
4	-0.32798	-2.2723	0.013793
5	0.182669	1.2656	0.105889
6	0.134462	0.9316	0.178109
7	-0.380672	-2.6374	0.005613
8	0.253804	1.7584	0.042526
9	-0.097646	-0.6765	0.250982
10	-0.193409	-1.34	0.093281
11	0.160544	1.1123	0.135779
12	-0.176372	-1.2219	0.113848
13	-0.115667	-0.8014	0.213435
14	0.09489	0.6574	0.257027
15	-0.058345	-0.4042	0.343921
16	-0.063258	-0.4383	0.331581
17	0.095343	0.6606	0.256028
18	-0.112064	-0.7764	0.22066
19	0.036285	0.2514	0.401294
20	0.093044	0.6446	0.26112
21	-0.081956	-0.5678	0.286405
22	-0.082869	-0.5741	0.284278
23	0.283971	1.9674	0.027465
24	-0.289766	-2.0076	0.025169
25	0.132466	0.9177	0.181669
26	0.077787	0.5389	0.296216
27	-0.202235	-1.4011	0.083804
28	0.195667	1.3556	0.090782
29	-0.032156	-0.2228	0.412326
30	-0.078563	-0.5443	0.294378
31	0.153221	1.0615	0.146877
32	-0.119323	-0.8267	0.206251
33	0.022424	0.1554	0.438594
34	0.092889	0.6436	0.261464
35	-0.112428	-0.7789	0.219924
36	0.001929	0.0134	0.494695
37	0.035007	0.2425	0.404699
38	-0.031539	-0.2185	0.413981
39	0.04122	0.2856	0.388215
40	-0.050256	-0.3482	0.364613
41	-0.005519	-0.0382	0.484828
42	0.061311	0.4248	0.336449
43	-0.051262	-0.3552	0.362014
44	-0.000818	-0.0057	0.497751
45	0.001451	0.01	0.496012
46	-0.002454	-0.017	0.493254
47	0.000188	0.0013	0.499484
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.418123	-2.8968	0.002831
2	-0.157648	-1.0922	0.140095
3	0.428886	2.9714	0.002311
4	0.017143	0.1188	0.452977
5	0.018619	0.129	0.448951
6	0.095417	0.6611	0.255866
7	-0.265031	-1.8362	0.036263
8	-0.123694	-0.857	0.197858
9	-0.072124	-0.4997	0.309789
10	-0.048707	-0.3375	0.368624
11	-0.068528	-0.4748	0.31855
12	-0.049771	-0.3448	0.365868
13	-0.13788	-0.9553	0.172116
14	-0.155166	-1.075	0.14387
15	0.126039	0.8732	0.193444
16	0.043056	0.2983	0.383381
17	0.020575	0.1425	0.443622
18	-0.090035	-0.6238	0.267862
19	-0.077454	-0.5366	0.297004
20	-0.027744	-0.1922	0.424193
21	0.005878	0.0407	0.483843
22	-0.213455	-1.4789	0.072855
23	0.175958	1.2191	0.114386
24	-0.113148	-0.7839	0.218472
25	-0.067937	-0.4707	0.32
26	-0.070729	-0.49	0.313174
27	0.014952	0.1036	0.458962
28	0.051346	0.3557	0.361798
29	-0.006445	-0.0447	0.482285
30	0.130973	0.9074	0.184363
31	-0.111822	-0.7747	0.221151
32	-0.082313	-0.5703	0.285574
33	-0.021648	-0.15	0.440703
34	-0.030815	-0.2135	0.415923
35	0.01609	0.1115	0.455853
36	-0.106654	-0.7389	0.231777
37	-0.028935	-0.2005	0.420982
38	-0.018304	-0.1268	0.449808
39	0.108654	0.7528	0.227629
40	-0.045778	-0.3172	0.376248
41	0.034395	0.2383	0.406334
42	0.045833	0.3175	0.376105
43	-0.043012	-0.298	0.383496
44	-0.114056	-0.7902	0.216647
45	-0.028873	-0.2	0.421147
46	-0.07064	-0.4894	0.313391
47	0.064641	0.4478	0.328139
48	NA	NA	NA
49	NA	NA	NA
50	NA	NA	NA
51	NA	NA	NA
52	NA	NA	NA
53	NA	NA	NA
54	NA	NA	NA
55	NA	NA	NA
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/1gc3r1292685291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/1gc3r1292685291.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/2r3ku1292685291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/2r3ku1292685291.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/3r3ku1292685291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685195r9sl9oqmsyokus7/3r3ku1292685291.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; 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 (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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