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non stationary time series mannen Q8 ACF

*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: Wed, 03 Dec 2008 05:19:30 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/03/t1228306843pjezau8m9k0b6ey.htm/, Retrieved Wed, 03 Dec 2008 12:20:45 +0000

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/2008/Dec/03/t1228306843pjezau8m9k0b6ey.htm/},
    year = {2008},
}
@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 = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

Feedback Forum:

2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply] 
test

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

non stationary time series mannen ACF

Dataseries X:

» Textbox « » Textfile « » CSV «

7.6 7.9 7.9 8.1 8.2 8 7.5 6.8 6.5 6.6 7.6 8 8 7.7 7.5 7.6 7.7 7.9 7.8 7.5 7.5 7.1 7.5 7.5 7.6 7.7 7.7 7.9 8.1 8.2 8.2 8.1 7.9 7.3 6.9 6.6 6.7 6.9 7 7.1 7.2 7.1 6.9 7 6.8 6.4 6.7 6.7 6.4 6.3 6.2 6.5 6.8 6.8 6.5 6.3 5.9 5.9 6.4 6.4 6.5

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.891865	6.9657	0
2	0.704516	5.5024	0
3	0.524264	4.0946	6.3e-05
4	0.395203	3.0866	0.001522
5	0.348983	2.7256	0.004182
6	0.343829	2.6854	0.004659
7	0.341357	2.6661	0.004905
8	0.334839	2.6152	0.005611
9	0.33968	2.653	0.005079
10	0.345652	2.6996	0.004485
11	0.345495	2.6984	0.0045
12	0.345467	2.6982	0.004502
13	0.304452	2.3778	0.010282
14	0.263436	2.0575	0.02196
15	0.192003	1.4996	0.069439
16	0.095279	0.7442	0.22982
17	0.020769	0.1622	0.435838
18	-0.031948	-0.2495	0.401898
19	-0.064999	-0.5077	0.306763
20	-0.083484	-0.652	0.258416
21	-0.092084	-0.7192	0.237383
22	-0.111855	-0.8736	0.192876
23	-0.132732	-1.0367	0.15199
24	-0.13234	-1.0336	0.152701
25	-0.131184	-1.0246	0.154804
26	-0.121747	-0.9509	0.17271
27	-0.129584	-1.0121	0.157748
28	-0.160534	-1.2538	0.107348
29	-0.197192	-1.5401	0.064352
30	-0.24442	-1.909	0.030486
31	-0.282158	-2.2037	0.015664
32	-0.299414	-2.3385	0.011328
33	-0.284805	-2.2244	0.014916
34	-0.252657	-1.9733	0.026498
35	-0.208438	-1.628	0.054345
36	-0.173367	-1.354	0.090359

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.891865	6.9657	0
2	-0.444374	-3.4707	0.00048
3	0.079414	0.6202	0.268704
4	0.096018	0.7499	0.228091
5	0.222608	1.7386	0.043573
6	-0.06063	-0.4735	0.318761
7	-0.006669	-0.0521	0.479314
8	0.073483	0.5739	0.284065
9	0.173448	1.3547	0.090259
10	-0.037595	-0.2936	0.38502
11	-0.007471	-0.0583	0.476831
12	0.083331	0.6508	0.258797
13	-0.189964	-1.4837	0.071523
14	0.185304	1.4473	0.076471
15	-0.367932	-2.8736	0.002788
16	0.021837	0.1706	0.432571
17	0.00692	0.054	0.478538
18	-0.039905	-0.3117	0.378176
19	-0.135603	-1.0591	0.146867
20	-0.042309	-0.3304	0.3711
21	0.033088	0.2584	0.398474
22	-0.114915	-0.8975	0.186486
23	0.029262	0.2285	0.409994
24	-0.009614	-0.0751	0.470194
25	0.099894	0.7802	0.219147
26	-0.1004	-0.7841	0.217994
27	0.022868	0.1786	0.42942
28	-0.064946	-0.5072	0.306907
29	0.035946	0.2808	0.389926
30	-0.085124	-0.6648	0.254328
31	-0.011024	-0.0861	0.465834
32	0.010412	0.0813	0.467728
33	0.094974	0.7418	0.230537
34	0.005079	0.0397	0.484243
35	-0.004746	-0.0371	0.485278
36	-0.061378	-0.4794	0.316693

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228306843pjezau8m9k0b6ey/1g9f11228306767.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228306843pjezau8m9k0b6ey/1g9f11228306767.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228306843pjezau8m9k0b6ey/2ay5m1228306767.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228306843pjezau8m9k0b6ey/2ay5m1228306767.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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