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ACF met d=1 en 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: Fri, 04 Dec 2009 07:20:26 -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/04/t1259937942sypga62biuv8cic.htm/, Retrieved Thu, 23 May 2013 09:02:32 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

t1259333395rhodj6bve5xvhiu (pk = 60852)

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	-0.099267	-0.6805	0.249751
2	0.117005	0.8021	0.213252
3	-0.264116	-1.8107	0.038292
4	-0.227563	-1.5601	0.062723
5	0.049122	0.3368	0.368897
6	0.061682	0.4229	0.33716
7	0.011689	0.0801	0.468234
8	0.096222	0.6597	0.256344
9	0.00715	0.049	0.480555
10	-0.256548	-1.7588	0.04256
11	0.066575	0.4564	0.325098
12	-0.409922	-2.8103	0.003597
13	0.233648	1.6018	0.057949
14	-0.022284	-0.1528	0.439617
15	0.060338	0.4137	0.340504
16	0.127765	0.8759	0.192766
17	-0.086348	-0.592	0.278354
18	-0.001936	-0.0133	0.494732
19	-0.048751	-0.3342	0.36985
20	0.00895	0.0614	0.475666
21	0.148913	1.0209	0.156266
22	0.244028	1.673	0.050489
23	-0.204703	-1.4034	0.083539
24	0.051522	0.3532	0.362752
25	-0.292137	-2.0028	0.025494
26	0.063883	0.438	0.33171
27	0.066223	0.454	0.325957
28	0.019375	0.1328	0.447448
29	0.073803	0.506	0.307621
30	0.010417	0.0714	0.471684
31	-0.003387	-0.0232	0.490787
32	-0.066037	-0.4527	0.326415
33	-0.039793	-0.2728	0.393097
34	-0.099045	-0.679	0.250228
35	0.162041	1.1109	0.136132
36	-0.013352	-0.0915	0.463727

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.099267	-0.6805	0.249751
2	0.108218	0.7419	0.230919
3	-0.248343	-1.7026	0.047629
4	-0.303406	-2.0801	0.0215
5	0.058488	0.401	0.345128
6	0.077962	0.5345	0.297765
7	-0.15301	-1.049	0.149774
8	0.032115	0.2202	0.413347
9	0.134452	0.9218	0.180682
10	-0.342485	-2.348	0.011568
11	-0.004394	-0.0301	0.488047
12	-0.314877	-2.1587	0.018006
13	0.018852	0.1292	0.448858
14	-0.076454	-0.5241	0.301321
15	-0.176248	-1.2083	0.116489
16	0.049385	0.3386	0.368222
17	-0.02991	-0.2051	0.419209
18	-0.064315	-0.4409	0.330645
19	-0.12017	-0.8238	0.207095
20	0.039902	0.2736	0.392812
21	0.1837	1.2594	0.107056
22	0.057065	0.3912	0.348701
23	-0.212897	-1.4595	0.075534
24	-0.085316	-0.5849	0.280707
25	-0.008537	-0.0585	0.476789
26	-0.022411	-0.1536	0.439275
27	-0.122331	-0.8387	0.202953
28	0.057004	0.3908	0.348855
29	0.014832	0.1017	0.459721
30	0.046308	0.3175	0.376145
31	0.08028	0.5504	0.292335
32	0.002469	0.0169	0.493282
33	0.073596	0.5045	0.308117
34	0.006401	0.0439	0.482592
35	-0.082839	-0.5679	0.286397
36	0.073895	0.5066	0.307403

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259937942sypga62biuv8cic/1iqs01259936425.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259937942sypga62biuv8cic/1iqs01259936425.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259937942sypga62biuv8cic/2sc6b1259936425.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259937942sypga62biuv8cic/2sc6b1259936425.ps (opens in new window)

Click here to open pdf file.

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')