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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: Wed, 29 Dec 2010 12:49:48 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun.htm/, Retrieved Wed, 29 Dec 2010 13:47:37 +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/2010/Dec/29/t1293626854p431ztme2nhpdun.htm/},
    year = {2010},
}
@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 = {2010},
    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 «
04.031636 03.702076 03.056167 03.280707 02.984728 03.693712 03.226317 02.190349 02.599515 03.080288 02.929672 02.922548 03.234943 02.983081 03.284389 03.806511 03.784579 02.645654 03.092081 03.204859 03.107225 03.466909 02.984404 03.218072 02.827310 03.182049 02.236319 02.033218 01.644804 01.627971 01.677559 02.330828 02.493615 02.257172 02.655517 02.298655 02.600402 03.045230 02.790583 03.227052 02.967479 02.938817 03.277961 03.423985 03.072646 02.754253 02.910431 03.174369 03.068387 03.089543 02.906654 02.931161 03.025660 02.939551 02.691019 03.198120 03.076390 02.863873 03.013802 03.053364 02.864753 03.057062 02.959365 03.252258 03.602988 03.497704 03.296867 03.602417 03.300100 03.401930 03.502591 03.402348 03.498551 03.199823 02.700064 02.801034 02.898628 02.800854 02.399942 02.402724 02.202331 02.102594 01.798293 01.202484 01.400201 01.200832 01.298083 01.099742 01.001377 00.836174
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8256787.29220
20.7049116.22560
30.6025345.32140
40.531524.69436e-06
50.4376113.86490.000114
60.2941752.59810.005602
70.1548921.3680.087625
80.0367770.32480.373098
9-0.027146-0.23980.405576
10-0.123245-1.08850.139869
11-0.211362-1.86670.032851
12-0.319344-2.82040.00304
13-0.300353-2.65260.004836
14-0.295928-2.61360.005374
15-0.253289-2.2370.014071
16-0.203221-1.79480.03828
17-0.176412-1.5580.061637
18-0.112507-0.99360.161736
19-0.089353-0.78910.216209
20-0.039506-0.34890.364049
210.0053580.04730.481189
220.0505220.44620.328344
230.0914490.80770.210872
240.1150191.01580.156427
250.110290.97410.166521
260.1094320.96650.168395
270.1078650.95260.171859
280.0779040.6880.246739
290.0303660.26820.394633
30-0.01701-0.15020.440487
31-0.03625-0.32010.374856
32-0.0578-0.51050.305581
33-0.091383-0.80710.21104
34-0.147406-1.30190.098399
35-0.225946-1.99550.02474
36-0.269747-2.38230.009819


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8256787.29220
20.0727920.64290.261093
30.0087470.07730.46931
40.0530870.46880.320243
5-0.088093-0.7780.219456
6-0.224998-1.98710.02521
7-0.138524-1.22340.112429
8-0.085348-0.75380.226626
90.0527330.46570.321355
10-0.117553-1.03820.151192
11-0.050804-0.44870.32745
12-0.153495-1.35560.089564
130.2485282.19490.015571
14-0.025692-0.22690.410545
150.1469221.29760.099128
160.1169461.03280.152435
17-0.044747-0.39520.346888
180.0018120.0160.493638
19-0.162806-1.43790.077237
20-0.021671-0.19140.424356
210.0545490.48180.31566
22-0.03373-0.29790.383286
230.0667530.58950.278598
24-0.061464-0.54280.294395
25-0.012649-0.11170.45567
26-0.026198-0.23140.408815
270.0468490.41380.340092
28-0.001529-0.01350.494632
29-0.109275-0.96510.16874
300.0242220.21390.415582
31-0.060894-0.53780.296122
320.0045790.04040.483921
33-0.025165-0.22230.41235
34-0.11017-0.9730.166783
35-0.100677-0.88920.188326
36-0.095636-0.84460.200448
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/17nsv1293626986.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/17nsv1293626986.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/2ixay1293626986.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/2ixay1293626986.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/3ixay1293626986.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293626854p431ztme2nhpdun/3ixay1293626986.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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')
 




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