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Workshop 8: Review

*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: Thu, 03 Dec 2009 08:24:08 -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/03/t1259853907kn2c5uqt4csvp5y.htm/, Retrieved Thu, 03 Dec 2009 16:25:09 +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/Dec/03/t1259853907kn2c5uqt4csvp5y.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:
RW8(10)
 
Dataseries X:
» Textbox « » Textfile « » CSV «
2.05 2.11 2.09 2.05 2.08 2.06 2.06 2.08 2.07 2.06 2.07 2.06 2.09 2.07 2.09 2.28 2.33 2.35 2.52 2.63 2.58 2.70 2.81 2.97 3.04 3.28 3.33 3.50 3.56 3.57 3.69 3.82 3.79 3.96 4.06 4.05 4.03 3.94 4.02 3.88 4.02 4.03 4.09 3.99 4.01 4.01 4.19 4.30 4.27 3.82 3.15 2.49 1.81 1.26 1.06 0.84 0.78 0.70 0.36 0.35
 
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
10.753395.78690
20.6239584.79276e-06
30.42833.28980.000847
40.2629312.01960.023987
50.1605681.23330.111168
60.1774841.36330.088987
70.1442281.10780.136214
80.1458451.12030.133572
90.0826440.63480.264005
100.0316040.24280.404519
110.0126240.0970.461541
120.0197740.15190.439898
130.0687120.52780.299814
140.0483340.37130.355888
150.0713730.54820.292802
16-0.002191-0.01680.493315
17-0.024915-0.19140.424444
18-0.076178-0.58510.280343
19-0.05571-0.42790.335134
20-0.104913-0.80590.211782
21-0.061226-0.47030.319942
22-0.10727-0.8240.206641
23-0.08744-0.67160.252217
24-0.14804-1.13710.130043
25-0.179086-1.37560.087075
26-0.165151-1.26860.104792
27-0.202405-1.55470.062683
28-0.204367-1.56980.060908
29-0.143782-1.10440.13695
30-0.1535-1.17910.121555
31-0.159215-1.2230.113105
32-0.135475-1.04060.151152
33-0.159592-1.22580.112563
34-0.167389-1.28570.101778
35-0.172774-1.32710.094794
36-0.138671-1.06510.145574
37-0.130177-0.99990.160718
38-0.089499-0.68750.247246
39-0.073805-0.56690.286464
40-0.074101-0.56920.285697
41-0.043524-0.33430.369664
42-0.049277-0.37850.353207
43-0.065985-0.50680.307077
44-0.039239-0.30140.382084
45-0.035394-0.27190.393337
46-0.039934-0.30670.380062
47-0.030203-0.2320.408673
48-0.043557-0.33460.369568
49-0.041133-0.31590.376579
50-0.031357-0.24090.405251
51-0.036156-0.27770.391101
52-0.022915-0.1760.430442
53-0.008902-0.06840.472859
54-0.01425-0.10950.456606
550.0005590.00430.498293
56-0.003069-0.02360.490636
57-0.011243-0.08640.465736
580.0006840.00530.497913
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.753395.78690
20.1303441.00120.160412
3-0.185176-1.42240.080093
4-0.110957-0.85230.198753
50.0486130.37340.355094
60.2506011.92490.029533
7-0.058404-0.44860.327677
8-0.066292-0.50920.306256
9-0.134193-1.03080.153431
100.0055610.04270.483036
110.1420151.09080.139889
120.0591150.45410.325721
130.0615450.47270.319074
14-0.221434-1.70090.047117
150.0453070.3480.364535
16-0.078459-0.60270.274523
170.0947590.72790.234791
18-0.03818-0.29330.385173
190.0016390.01260.494998
20-0.165517-1.27140.104294
210.0504970.38790.349751
22-0.013524-0.10390.458809
230.0780210.59930.275637
24-0.154293-1.18520.120355
25-0.165532-1.27150.104275
260.134321.03170.153205
27-0.105508-0.81040.210477
280.0284840.21880.413784
290.1042740.80090.213189
30-0.135212-1.03860.151618
31-0.097545-0.74930.228339
32-0.007012-0.05390.478613
330.1162160.89270.18783
34-0.115137-0.88440.19004
35-0.017531-0.13470.446671
36-0.019646-0.15090.440283
370.0391570.30080.382323
380.0052050.040.484122
390.0460140.35340.36251
40-0.071938-0.55260.291323
410.0467830.35930.360309
42-0.100538-0.77220.221526
430.0002490.00190.499242
440.0479220.36810.35706
45-0.015426-0.11850.453042
460.0112640.08650.465674
47-0.096934-0.74460.229746
48-0.029001-0.22280.412245
490.0401050.3080.379565
500.063410.48710.314011
51-0.050289-0.38630.350342
52-0.139332-1.07020.144437
530.0695660.53430.297555
54-0.015171-0.11650.453813
550.0440580.33840.368126
56-0.036144-0.27760.391134
57-0.014488-0.11130.455884
58-0.079824-0.61310.27107
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259853907kn2c5uqt4csvp5y/10u7x1259853847.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259853907kn2c5uqt4csvp5y/10u7x1259853847.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/03/t1259853907kn2c5uqt4csvp5y/2sata1259853847.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259853907kn2c5uqt4csvp5y/2sata1259853847.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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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