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*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, 08 Dec 2009 11:38:48 -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/08/t1260297562nn4n21z98n63nz6.htm/, Retrieved Sat, 25 May 2013 05:58:07 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

t1260297221whf3lvf6n4h16q9 (pk = 64772)

Estimated Impact

Dataseries X:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

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	0.102198	1.901	0.029066
2	0.007114	0.1323	0.4474
3	0.072118	1.3415	0.090322
4	-0.202955	-3.7752	9.4e-05
5	-0.170566	-3.1727	0.000823
6	0.049778	0.9259	0.177566
7	0.196906	3.6627	0.000144
8	0.128926	2.3982	0.008503
9	0.017479	0.3251	0.372639
10	-0.001595	-0.0297	0.488177
11	-0.063555	-1.1822	0.11897
12	-0.556171	-10.3454	0
13	-0.064594	-1.2015	0.115188
14	-0.038871	-0.723	0.23507
15	-0.071012	-1.3209	0.093704
16	0.109337	2.0338	0.021368
17	0.050411	0.9377	0.174525
18	-0.131048	-2.4376	0.007643
19	-0.188466	-3.5057	0.000258
20	-0.026326	-0.4897	0.312334
21	-0.096174	-1.7889	0.03725
22	0.078893	1.4675	0.071576
23	0.059681	1.1101	0.133859
24	0.06454	1.2005	0.115379
25	0.001893	0.0352	0.485963

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.102198	1.901	0.029066
2	-0.003365	-0.0626	0.47506
3	0.072491	1.3484	0.089205
4	-0.221162	-4.1138	2.4e-05
5	-0.131997	-2.4553	0.007284
6	0.07952	1.4792	0.070004
7	0.240404	4.4718	5e-06
8	0.084854	1.5784	0.057696
9	-0.101863	-1.8948	0.029479
10	-0.064388	-1.1977	0.115929
11	0.030193	0.5616	0.287368
12	-0.505022	-9.3939	0
13	0.023039	0.4286	0.334256
14	-0.085142	-1.5837	0.057084
15	0.032248	0.5998	0.274502
16	-0.113063	-2.1031	0.01809
17	-0.08738	-1.6254	0.052498
18	-0.122831	-2.2848	0.011465
19	-0.019388	-0.3606	0.359295
20	0.10178	1.8932	0.029581
21	-0.097491	-1.8134	0.035316
22	0.106876	1.988	0.0238
23	-0.044159	-0.8214	0.205989
24	-0.312113	-5.8056	0
25	0.005922	0.1101	0.456178

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297562nn4n21z98n63nz6/1q7lz1260297527.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297562nn4n21z98n63nz6/1q7lz1260297527.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297562nn4n21z98n63nz6/2idre1260297527.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297562nn4n21z98n63nz6/2idre1260297527.ps (opens in new window)

Click here to open pdf file.

Parameters (Session):

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

Parameters (R input):

par1 = Default ; 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')