Home » date » 2010 » Dec » 24 »

Kristof Nagels

*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, 24 Dec 2010 15:05:06 +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/24/t1293202966m7zjzmlv9weh7mq.htm/, Retrieved Fri, 24 Dec 2010 16:02:49 +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/24/t1293202966m7zjzmlv9weh7mq.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 «
15 14.4 13 13.7 13.6 15.2 12.9 14 14.1 13.2 11.3 13.3 14.4 13.3 11.6 13.2 13.1 14.6 14 14.3 13.8 13.7 11 14.4 15.6 13.7 12.6 13.2 13.3 14.3 14 13.4 13.9 13.7 10.5 14.5 15 13.5 13.5 13.2 13.8 16.2 14.7 13.9 16 14.4 12.3 15.9 15.9 15.5 15.1 14.5 15.1 17.4 16.2 15.6 17.2 14.9 13.8 17.5 16.2 17.5 16.6 16.2 16.6 19.6 15.9 18 18.3 16.3 14.9 18.2 18.4 18.5 16 17.4 17.2 19.6 17.2 18.3 19.3 18.1 16.2 18.4 20.5 19 16.5 18.7 19 19.2 20.5 19.3 20.6 20.1 16.1 20.4 19.7 15.6 14.4 13.7 14.1 15 14.2 13.6 15.4 14.8 12.5 16.2 16.1 16 15.8 15.2 15.7 18.9 17.4 17 19.8 17.7 16 19.6 19.7
 
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'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.406324-3.98116.7e-05
20.092560.90690.183367
30.3691613.6170.000239
4-0.282376-2.76670.003397
50.2203782.15930.016661
60.0915290.89680.186034
7-0.32429-3.17740.001
80.2551192.49960.007064
9-0.206531-2.02360.022896
10-0.060691-0.59460.276739
110.0918080.89950.185311
12-0.291732-2.85840.002611
130.0785940.77010.221578
14-0.057191-0.56040.288272
15-0.006826-0.06690.473407
16-0.078576-0.76990.221629
170.010090.09890.460727
180.0206690.20250.419971
19-0.037097-0.36350.358523
200.0243750.23880.405873
210.0874730.85710.196775
22-0.21913-2.1470.017155
230.3469983.39990.000492
24-0.193864-1.89950.030252
25-0.011167-0.10940.456551
260.1802761.76630.040259
27-0.186859-1.83080.035114
280.1222131.19740.117042
290.0359020.35180.362891
30-0.14584-1.42890.078135
310.1698261.66390.049692
32-0.082645-0.80970.210043
33-0.02473-0.24230.40453
340.09830.96310.168948
35-0.13743-1.34650.09065
360.0330650.3240.373334
370.0323660.31710.37592
38-0.05748-0.56320.287309
390.0318290.31190.377913
40-0.052223-0.51170.305026
410.0782580.76680.222551
42-0.045863-0.44940.327093
43-0.029169-0.28580.387823
440.1282681.25680.105944
45-0.155112-1.51980.065926
460.1301591.27530.102641
470.0269650.26420.396097
48-0.124961-1.22440.111906
490.1430281.40140.082162
50-0.069479-0.68080.248833
51-0.040308-0.39490.346885
520.1277591.25180.106847
53-0.183094-1.79390.037985
540.0930560.91180.182091
550.0085650.08390.466647
56-0.120595-1.18160.120144
570.0710680.69630.243956
58-0.03303-0.32360.373463
59-0.098335-0.96350.168864
600.0984690.96480.168537


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.406324-3.98116.7e-05
2-0.086884-0.85130.198364
30.4522524.43111.2e-05
40.0598770.58670.279401
50.0612080.59970.275055
60.0796870.78080.218431
7-0.28235-2.76650.003399
8-0.142047-1.39180.083604
9-0.202955-1.98850.024799
10-0.022941-0.22480.411315
110.0133940.13120.447931
12-0.113199-1.10910.135076
13-0.041431-0.40590.342845
14-0.084137-0.82440.205885
150.2420022.37110.009866
16-0.104925-1.02810.153254
17-0.024565-0.24070.405155
18-0.013152-0.12890.448866
19-0.07612-0.74580.228798
20-0.059923-0.58710.279249
210.0428670.420.337707
22-0.165302-1.61960.054297
230.2042312.0010.024105
24-0.024692-0.24190.404675
25-0.05986-0.58650.279455
26-0.087162-0.8540.197614
270.0382090.37440.354479
280.0250460.24540.403336
29-0.070669-0.69240.245176
300.078150.76570.222864
310.0042910.0420.483275
32-0.000414-0.00410.498387
330.0079330.07770.469105
34-0.112029-1.09770.137551
350.0547090.5360.296587
36-0.145674-1.42730.078368
370.0316590.31020.378543
38-0.037052-0.3630.358689
390.1564331.53270.064316
40-0.054601-0.5350.296949
410.1187571.16360.12374
42-0.023927-0.23440.407572
43-0.077868-0.76290.223684
440.0244720.23980.405509
45-0.040597-0.39780.345842
46-0.034947-0.34240.366396
470.0957340.9380.175299
48-0.010328-0.10120.459805
49-0.019055-0.18670.426146
50-0.023528-0.23050.409085
510.0235320.23060.409071
52-0.042117-0.41270.340388
53-0.031413-0.30780.379456
54-0.024279-0.23790.406239
550.014790.14490.442541
56-0.017979-0.17620.430271
57-0.014344-0.14050.444265
58-0.053651-0.52570.300163
590.0359890.35260.362575
60-0.098839-0.96840.167635
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/112nl1293203102.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/112nl1293203102.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/2cbmo1293203102.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/2cbmo1293203102.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/3cbmo1293203102.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202966m7zjzmlv9weh7mq/3cbmo1293203102.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; 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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