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WS08 - PACF d = 1/ D = 1 / lambda = 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: Wed, 25 Nov 2009 13:49:28 -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/Nov/25/t1259182322pbaz3e7bi27jbr9.htm/, Retrieved Wed, 25 Nov 2009 21:52:05 +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/Nov/25/t1259182322pbaz3e7bi27jbr9.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 «
423.4 404.1 500 472.6 496.1 562 434.8 538.2 577.6 518.1 625.2 561.2 523.3 536.1 607.3 637.3 606.9 652.9 617.2 670.4 729.9 677.2 710 844.3 748.2 653.9 742.6 854.2 808.4 1819 1936.5 1966.1 2083.1 1620.1 1527.6 1795 1685.1 1851.8 2164.4 1981.8 1726.5 2144.6 1758.2 1672.9 1837.3 1596.1 1446 1898.4 1964.1 1755.9 2255.3 1881.2 2117.9 1656.5 1544.1 2098.9 2133.3 1963.5 1801.2 2365.4 1936.5 1667.6 1983.5 2058.6 2448.3 1858.1 1625.4 2130.6 2515.7 2230.2 2086.9 2235 2100.2 2288.6 2490 2573.7 2543.8 2004.7 2390 2338.4 2724.5 2292.5 2386 2477.9 2337 2605.1 2560.8 2839.3 2407.2 2085.2 2735.6 2798.7 3053.2 2405 2471.9 2727.3 2790.7 2385.4 3206.6 2705.6 3518.4 1954.9 2584.3 2535.8 2685.9 2866 2236.6 2934.9 2668.6 2371.2 3165.9 2887.2 3112.2 2671.2 2432.6 2812.3 3095.7 2862.9 2607.3 2862.5
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.514912-5.32630
20.266542.75710.003429
3-0.192242-1.98860.024651
4-0.078614-0.81320.208957
50.1515521.56770.059956
6-0.16584-1.71550.044577
70.0771490.7980.213309
8-0.029416-0.30430.380751
90.170171.76030.040611
10-0.124527-1.28810.100242
110.1443751.49340.069135
12-0.31498-3.25820.000752
130.2185142.26030.012913
14-0.242314-2.50650.006849
150.1356011.40270.081805
16-0.073744-0.76280.223628
17-0.010944-0.11320.455041
180.2187752.2630.012826
19-0.190979-1.97550.025393
200.1364541.41150.0805
21-0.113685-1.1760.121108
220.0453220.46880.320076
230.0615850.6370.26273
24-0.155999-1.61370.054773
250.0044930.04650.481509
260.0979571.01330.156608
270.0282360.29210.385399
280.0470610.48680.313697
29-0.119444-1.23550.109668
300.0327470.33870.367737
31-0.063591-0.65780.256041
320.0401780.41560.339265
33-0.000164-0.00170.499323
34-0.084237-0.87140.192755
350.1558921.61260.054893
36-0.090658-0.93780.175236
370.0615890.63710.262716
38-0.051825-0.53610.296508
39-0.004163-0.04310.482865
400.0059420.06150.475554
410.0671140.69420.24452
42-0.10686-1.10540.13574
430.0985921.01980.155051
440.0012620.01310.494805
45-0.027395-0.28340.388719
460.0816030.84410.200245
47-0.182114-1.88380.031153
480.1550181.60350.055884
49-0.108443-1.12170.132241
500.1017141.05210.147554
51-0.099541-1.02970.152747
520.0336950.34850.36406
530.0397720.41140.3408
54-0.059053-0.61080.271299
550.0841790.87080.192919
56-0.086885-0.89870.185404
57-0.007439-0.0770.469402
580.0099790.10320.45899
590.0027480.02840.488689
600.0008960.00930.496313


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.514912-5.32630
20.0019120.01980.492128
3-0.073857-0.7640.223279
4-0.281599-2.91290.00218
50.0206510.21360.415626
6-0.071455-0.73910.23072
7-0.155699-1.61060.05511
8-0.038859-0.4020.344258
90.2401152.48380.007276
10-0.020151-0.20840.417641
110.0882520.91290.181676
12-0.194251-2.00930.023509
13-0.021988-0.22740.410257
14-0.206007-2.1310.017691
15-0.107316-1.11010.134725
16-0.162032-1.67610.048322
17-0.143392-1.48330.070473
180.0738250.76360.223379
19-0.013571-0.14040.444313
20-0.066403-0.68690.246823
210.1172491.21280.113932
220.0572860.59260.277361
230.1753041.81340.03629
24-0.141687-1.46560.072842
25-0.189988-1.96530.025988
26-0.049845-0.51560.303598
270.0541290.55990.288354
28-0.087842-0.90860.182791
29-0.184429-1.90770.029552
300.0256180.2650.395764
31-0.155796-1.61160.055001
32-0.063651-0.65840.255845
330.1323431.3690.086938
34-0.053966-0.55820.288929
350.1191761.23280.110182
36-0.052278-0.54080.294897
37-0.065916-0.68180.248408
38-0.079073-0.81790.207606
390.003920.04060.483864
40-0.071929-0.7440.229241
41-0.040019-0.4140.339867
42-0.01013-0.10480.458371
43-0.050288-0.52020.302006
440.0582260.60230.274127
450.0057280.05930.476431
460.0332620.34410.365736
470.054110.55970.288422
48-0.073103-0.75620.225599
49-0.078183-0.80870.210233
50-0.048118-0.49770.309846
51-0.019136-0.19790.421731
52-0.052499-0.54310.294109
53-0.045782-0.47360.318385
54-0.037768-0.39070.348407
550.0109930.11370.454841
560.1165221.20530.11537
57-0.047335-0.48960.312698
58-0.030958-0.32020.374709
59-0.011461-0.11860.452925
60-0.015635-0.16170.435912
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/25/t1259182322pbaz3e7bi27jbr9/1dxdg1259182166.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/25/t1259182322pbaz3e7bi27jbr9/1dxdg1259182166.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/25/t1259182322pbaz3e7bi27jbr9/2khm81259182166.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/25/t1259182322pbaz3e7bi27jbr9/2khm81259182166.ps (open in new window)


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





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