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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 05:23:08 -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/t1228307043r4a5oi9rzuersni.htm/, Retrieved Wed, 03 Dec 2008 12:24:05 +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/t1228307043r4a5oi9rzuersni.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 Q8 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	0.447933	3.1034	0.001602
2	-0.068643	-0.4756	0.318267
3	-0.346068	-2.3976	0.01022
4	-0.457542	-3.1699	0.001327
5	-0.176114	-1.2202	0.114183
6	0.058869	0.4079	0.342595
7	0.136082	0.9428	0.175251
8	0.137737	0.9543	0.172363
9	-0.059277	-0.4107	0.341567
10	-0.043203	-0.2993	0.382994
11	0.008639	0.0599	0.476261
12	-0.059857	-0.4147	0.340104
13	0.071009	0.492	0.312494
14	0.07918	0.5486	0.29292
15	-0.041722	-0.2891	0.386892
16	-0.090947	-0.6301	0.265809
17	-0.166236	-1.1517	0.12757
18	-0.064623	-0.4477	0.328185
19	0.099516	0.6895	0.246924
20	0.186573	1.2926	0.101166
21	0.235781	1.6335	0.05445
22	0.001889	0.0131	0.494806
23	-0.228537	-1.5834	0.059954
24	-0.273049	-1.8917	0.032284
25	-0.151194	-1.0475	0.150057
26	0.113042	0.7832	0.218684
27	0.251811	1.7446	0.043728
28	0.130216	0.9022	0.185737
29	0.028724	0.199	0.421549
30	-0.15096	-1.0459	0.150427
31	-0.126984	-0.8798	0.191683
32	0.001802	0.0125	0.495045
33	0.032433	0.2247	0.411583
34	0.069025	0.4782	0.317333
35	0.055014	0.3811	0.352389
36	-0.058124	-0.4027	0.34448

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.447933	3.1034	0.001602
2	-0.33688	-2.334	0.011915
3	-0.217406	-1.5062	0.06928
4	-0.285059	-1.9749	0.027021
5	0.108241	0.7499	0.228483
6	-0.093247	-0.646	0.260667
7	-0.059286	-0.4107	0.341543
8	-0.034298	-0.2376	0.406592
9	-0.16984	-1.1767	0.122562
10	0.134752	0.9336	0.177595
11	-0.042903	-0.2972	0.383782
12	-0.126887	-0.8791	0.191864
13	0.130886	0.9068	0.18452
14	-0.00355	-0.0246	0.490241
15	-0.097422	-0.675	0.25147
16	-0.091986	-0.6373	0.263479
17	-0.071934	-0.4984	0.310247
18	0.028326	0.1962	0.422622
19	0.031605	0.219	0.413803
20	0.077815	0.5391	0.296148
21	0.04333	0.3002	0.38266
22	-0.117357	-0.8131	0.210096
23	-0.056935	-0.3945	0.347496
24	-0.126705	-0.8778	0.192201
25	0.072397	0.5016	0.309129
26	0.054628	0.3785	0.353374
27	-0.008544	-0.0592	0.476522
28	-0.1109	-0.7683	0.223026
29	0.070543	0.4887	0.313627
30	-0.084338	-0.5843	0.280874
31	0.067628	0.4685	0.320759
32	-0.036901	-0.2557	0.399654
33	-0.015942	-0.1104	0.456257
34	-0.025325	-0.1755	0.43073
35	0.059926	0.4152	0.33993
36	-0.088945	-0.6162	0.270327

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228307043r4a5oi9rzuersni/13mz91228306986.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228307043r4a5oi9rzuersni/13mz91228306986.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228307043r4a5oi9rzuersni/2y0zt1228306986.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228307043r4a5oi9rzuersni/2y0zt1228306986.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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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