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ACF d=1 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: Tue, 15 Dec 2009 12:35:54 -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/15/t1260905828goz2zww6m0ram2z.htm/, Retrieved Tue, 15 Dec 2009 20:37:10 +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/15/t1260905828goz2zww6m0ram2z.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

103.1 102.0 104.7 86.0 92.1 106.9 112.6 101.7 92.0 97.4 97.0 105.4 102.7 98.1 104.5 87.4 89.9 109.8 111.7 98.6 96.9 95.1 97.0 112.7 102.9 97.4 111.4 87.4 96.8 114.1 110.3 103.9 101.6 94.6 95.9 104.7 102.8 98.1 113.9 80.9 95.7 113.2 105.9 108.8 102.3 99.0 100.7 115.5 100.7 109.9 114.6 85.4 100.5 114.8 116.5 112.9 102.0 106.0 105.3 118.8 106.1 109.3 117.2 92.5 104.2 112.5 122.4 113.3 100.0 110.7 112.8 109.8 117.3 109.1 115.9 96.0 99.8 116.8 115.7 99.4 94.3 91.0 93.2 103.1 94.1 91.8 102.7 82.6 89.1 104.5

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	-0.606971	-5.3261	0
2	0.002185	0.0192	0.492378
3	0.37674	3.3059	0.00072
4	-0.369937	-3.2462	0.000866
5	0.1216	1.067	0.144645
6	0.182728	1.6034	0.056467
7	-0.311312	-2.7318	0.003904
8	0.193724	1.6999	0.046591
9	-0.017904	-0.1571	0.437785
10	-0.149121	-1.3085	0.097293
11	0.232267	2.0381	0.022485
12	-0.204834	-1.7974	0.038095
13	0.051077	0.4482	0.327634
14	0.04987	0.4376	0.331447
15	-0.006313	-0.0554	0.477982
16	-0.099129	-0.8699	0.193542
17	0.128922	1.1313	0.130723
18	-0.004234	-0.0372	0.485228
19	-0.136381	-1.1967	0.117539
20	0.115928	1.0173	0.156107
21	0.079336	0.6962	0.24421
22	-0.310477	-2.7244	0.003984
23	0.41855	3.6728	0.00022
24	-0.275257	-2.4154	0.009045
25	-0.039439	-0.3461	0.365116
26	0.267681	2.3489	0.010698
27	-0.223958	-1.9652	0.026498
28	0.012373	0.1086	0.456913
29	0.163694	1.4364	0.077468
30	-0.200553	-1.7598	0.041203
31	0.095537	0.8383	0.202219
32	0.083728	0.7347	0.232375
33	-0.217306	-1.9069	0.030135
34	0.216134	1.8966	0.030818
35	-0.142012	-1.2461	0.108244
36	0.007436	0.0652	0.474073

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.606971	-5.3261	0
2	-0.579856	-5.0882	1e-06
3	0.064116	0.5626	0.287665
4	0.04161	0.3651	0.358007
5	-0.01962	-0.1722	0.431881
6	0.156264	1.3712	0.087146
7	0.00751	0.0659	0.473813
8	-0.045526	-0.3995	0.34532
9	-0.128653	-1.1289	0.131216
10	-0.157725	-1.384	0.085174
11	0.063586	0.558	0.289245
12	-0.053259	-0.4673	0.320785
13	-0.031166	-0.2735	0.392609
14	-0.135362	-1.1878	0.119282
15	0.153809	1.3497	0.090538
16	-0.048335	-0.4241	0.336322
17	-0.05516	-0.484	0.31487
18	0.163015	1.4305	0.078316
19	0.010812	0.0949	0.46233
20	-0.155722	-1.3665	0.087887
21	0.09097	0.7983	0.213588
22	-0.209281	-1.8364	0.035076
23	0.223177	1.9584	0.026904
24	-0.03101	-0.2721	0.393133
25	-0.008124	-0.0713	0.471678
26	-0.051057	-0.448	0.327696
27	0.166337	1.4596	0.074233
28	-0.034285	-0.3008	0.38217
29	-0.094489	-0.8291	0.204794
30	0.055587	0.4878	0.313548
31	0.030704	0.2694	0.39416
32	-0.033919	-0.2976	0.383391
33	-0.003622	-0.0318	0.487364
34	-0.047172	-0.4139	0.340037
35	-0.015834	-0.1389	0.444929
36	-0.120799	-1.06	0.146228

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260905828goz2zww6m0ram2z/16jf01260905752.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260905828goz2zww6m0ram2z/16jf01260905752.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260905828goz2zww6m0ram2z/2wdjp1260905752.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260905828goz2zww6m0ram2z/2wdjp1260905752.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

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