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WS 9 (P)ACF 2

*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: Thu, 03 Dec 2009 11:57:52 -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/03/t12598667425x12pkrxfcrml6t.htm/, Retrieved Thu, 03 Dec 2009 19:59:04 +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/03/t12598667425x12pkrxfcrml6t.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 «

106,9 107,5 116,1 102 111,2 111,8 91,2 93 105,4 111,6 104,6 91,6 98,3 97,7 106,3 102,3 106,6 108,1 93,8 88,2 108,9 114,2 102,5 94,2 97,4 98,5 106,5 102,9 97,1 103,7 93,4 85,8 108,6 110,2 101,2 101,2 96,9 99,4 118,7 108 101,2 119,9 94,8 95,3 118 115,9 111,4 108,2 108,8 109,5 124,8 115,3 109,5 124,2 92,9 98,4 120,9 111,7 116,1 109,4 111,7 114,3 133,7 114,3 126,5 131 104 108,9 128,5 132,4 128 116,4 120,9 118,6 133,1 121,1 127,6 135,4 114,9 114,3 128,9 138,9 129,4 115 128 127 128,8 137,9 128,4 135,9 122,2 113,1 136,2 138 115,2 111

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	0.386222	3.5398	0.000328
2	0.412559	3.7812	0.000146
3	0.520422	4.7697	4e-06
4	0.185023	1.6958	0.046817
5	0.286189	2.623	0.005175
6	0.261743	2.3989	0.009329
7	0.028507	0.2613	0.397263
8	0.118698	1.0879	0.139879
9	0.141595	1.2977	0.098964
10	-0.048776	-0.447	0.328
11	0.055354	0.5073	0.306627
12	0.069523	0.6372	0.262866
13	-0.06588	-0.6038	0.273802
14	0.093801	0.8597	0.196199
15	0.06294	0.5769	0.282791
16	-0.037566	-0.3443	0.365742
17	0.102306	0.9377	0.175556
18	0.116543	1.0681	0.144259
19	-0.037951	-0.3478	0.364421
20	0.140749	1.29	0.100297
21	0.114174	1.0464	0.149184
22	-0.124965	-1.1453	0.127664
23	0.167216	1.5326	0.064571
24	-0.115425	-1.0579	0.146571
25	-0.103842	-0.9517	0.171982
26	0.061581	0.5644	0.286993
27	-0.139942	-1.2826	0.101581
28	-0.063059	-0.5779	0.282423
29	-0.026874	-0.2463	0.403024
30	-0.160494	-1.471	0.07252
31	-0.0798	-0.7314	0.233291
32	-0.072887	-0.668	0.252975
33	-0.213805	-1.9596	0.026682
34	-0.115066	-1.0546	0.147317
35	-0.118713	-1.088	0.139849
36	-0.224317	-2.0559	0.021449

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.386222	3.5398	0.000328
2	0.309569	2.8372	0.002851
3	0.378069	3.4651	0.000419
4	-0.189563	-1.7374	0.042993
5	0.0339	0.3107	0.3784
6	0.022444	0.2057	0.418762
7	-0.136349	-1.2497	0.107448
8	-0.045883	-0.4205	0.337588
9	0.127081	1.1647	0.123716
10	-0.077012	-0.7058	0.241125
11	-0.020138	-0.1846	0.427005
12	0.068451	0.6274	0.26606
13	-0.020759	-0.1903	0.424783
14	0.058436	0.5356	0.296835
15	0.041872	0.3838	0.351062
16	-0.032638	-0.2991	0.382788
17	0.002899	0.0266	0.489434
18	0.131832	1.2083	0.115169
19	-0.117589	-1.0777	0.142122
20	0.046986	0.4306	0.333919
21	0.082822	0.7591	0.224965
22	-0.238028	-2.1816	0.015968
23	0.11686	1.071	0.14361
24	-0.220718	-2.0229	0.023131
25	0.082089	0.7524	0.226968
26	-0.023048	-0.2112	0.416607
27	0.058266	0.534	0.29737
28	0.005009	0.0459	0.481747
29	-0.078627	-0.7206	0.23657
30	-0.034698	-0.318	0.375631
31	0.002683	0.0246	0.49022
32	-0.086215	-0.7902	0.215827
33	-0.083884	-0.7688	0.222083
34	0.011557	0.1059	0.45795
35	-0.068743	-0.63	0.265188
36	-0.011181	-0.1025	0.459311

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598667425x12pkrxfcrml6t/1vbxc1259866670.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598667425x12pkrxfcrml6t/1vbxc1259866670.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598667425x12pkrxfcrml6t/2lk371259866670.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598667425x12pkrxfcrml6t/2lk371259866670.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 0.0 ; 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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