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Paper; stationair maken via ACF D=1

*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, 19 Dec 2009 15:29:28 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/19/t12612619148qutdtmrkp4l1iz.htm/, Retrieved Sat, 19 Dec 2009 23:31:57 +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/2009/Dec/19/t12612619148qutdtmrkp4l1iz.htm/},
    year = {2009},
}
@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 = {2009},
    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:

Shw Paper; stationair maken via ACF D=1

Dataseries X:

» Textbox « » Textfile « » CSV «

152,60 153,32 165,50 139,18 136,53 115,92 96,65 83,77 84,66 106,03 86,92 54,66 151,66 121,27 132,95 119,64 122,16 117,44 106,69 87,45 80,98 110,30 87,01 55,73 146,00 137,54 138,54 135,62 107,27 99,04 91,36 68,35 82,59 98,41 71,25 47,58 130,83 113,60 125,69 113,60 97,12 104,43 91,84 75,11 89,24 110,23 78,42 68,45 122,81 129,66 159,06 139,03 102,16 113,59 81,46 77,36 87,57 101,23 87,21 64,94 133,12 117,99 135,90 125,67 108,03 128,31 84,74 86,38 92,24 95,83 92,33 54,27

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.526923	4.0815	6.7e-05
2	0.342072	2.6497	0.005142
3	0.145228	1.1249	0.132549
4	0.029591	0.2292	0.409741
5	0.072545	0.5619	0.288129
6	0.081419	0.6307	0.265325
7	0.02805	0.2173	0.414365
8	0.02994	0.2319	0.408695
9	0.020894	0.1618	0.435987
10	-0.194613	-1.5075	0.06847
11	-0.34585	-2.6789	0.004758
12	-0.445322	-3.4494	0.000517
13	-0.325296	-2.5197	0.007212
14	-0.12884	-0.998	0.161146
15	0.039571	0.3065	0.380136
16	-0.077499	-0.6003	0.275281
17	0.026623	0.2062	0.418659
18	0.012621	0.0978	0.461225
19	-0.049583	-0.3841	0.351143
20	0.050727	0.3929	0.347882
21	-0.030367	-0.2352	0.407419
22	0.063556	0.4923	0.312151
23	0.244509	1.894	0.031527
24	0.276764	2.1438	0.018056
25	0.215928	1.6726	0.04981
26	0.16835	1.304	0.098601
27	-0.023495	-0.182	0.4281
28	-0.017921	-0.1388	0.445032
29	-0.071811	-0.5562	0.290055
30	-0.122066	-0.9455	0.174092
31	-0.089738	-0.6951	0.244834
32	-0.009644	-0.0747	0.47035
33	0.006804	0.0527	0.479071
34	-0.101933	-0.7896	0.216444
35	-0.14557	-1.1276	0.131993
36	-0.31385	-2.4311	0.009029

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.526923	4.0815	6.7e-05
2	0.089187	0.6908	0.246165
3	-0.092013	-0.7127	0.239388
4	-0.054085	-0.4189	0.338376
5	0.12531	0.9706	0.167811
6	0.038352	0.2971	0.383718
7	-0.085253	-0.6604	0.255773
8	0.01972	0.1528	0.439553
9	0.03714	0.2877	0.38729
10	-0.309419	-2.3967	0.009837
11	-0.267052	-2.0686	0.021451
12	-0.148601	-1.1511	0.127137
13	0.110803	0.8583	0.197078
14	0.119767	0.9277	0.178637
15	0.127092	0.9845	0.164424
16	-0.22008	-1.7047	0.046709
17	0.188817	1.4626	0.074402
18	0.09269	0.718	0.237779
19	-0.12749	-0.9875	0.163674
20	0.081602	0.6321	0.264867
21	-0.088204	-0.6832	0.248547
22	-0.037014	-0.2867	0.387661
23	0.09498	0.7357	0.232386
24	0.0335	0.2595	0.398073
25	0.068259	0.5287	0.29947
26	0.074286	0.5754	0.28358
27	-0.17795	-1.3784	0.086599
28	-0.021375	-0.1656	0.434525
29	-0.087214	-0.6756	0.250959
30	-0.061135	-0.4735	0.318771
31	0.034349	0.2661	0.395549
32	0.008811	0.0682	0.472908
33	0.056131	0.4348	0.332637
34	-0.114286	-0.8853	0.189777
35	-0.013499	-0.1046	0.458537
36	0.003275	0.0254	0.489921

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612619148qutdtmrkp4l1iz/1ufr71261261766.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612619148qutdtmrkp4l1iz/1ufr71261261766.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612619148qutdtmrkp4l1iz/281i91261261766.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612619148qutdtmrkp4l1iz/281i91261261766.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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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