Home » date » 2008 » Dec » 19 »

acf prof bach L = 1 , 0,0

*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, 19 Dec 2008 08:35:04 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/19/t1229700993e0ldwct6hhtoxjo.htm/, Retrieved Fri, 19 Dec 2008 16:36:35 +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/2008/Dec/19/t1229700993e0ldwct6hhtoxjo.htm/},
    year = {2008},
}
@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 = {2008},
    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 «
13363 12530 11420 10948 10173 10602 16094 19631 17140 14345 12632 12894 11808 10673 9939 9890 9283 10131 15864 19283 16203 13919 11937 11795 11268 10522 9929 9725 9372 10068 16230 19115 18351 16265 14103 14115 13327 12618 12129 11775 11493 12470 20792 22337 21325 18581 16475 16581 15745 14453 13712 13766 13336 15346 24446 26178 24628 21282 18850 18822 18060 17536 16417 15842 15188 16905 25430 27962 26607 23364 20827 20506 19181 18016 17354 16256 15770 17538 26899 28915 25247 22856 19980 19856 16994 16839 15618 15883 15513 17106 25272 26731 22891 19583 16939 16757 15435 14786 13680 13208 12707 14277 22436 23229 18241 16145 13994 14780 13100 12329 12463 11532 10784 13106 19491 20418 16094 14491 13067
 
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
10.8182288.92580
20.5034165.49160
30.2581592.81620.002845
40.128661.40350.081534
50.0731740.79820.213164
60.040750.44450.328735
70.0640710.69890.24298
80.1168771.2750.102401
90.23552.5690.005717
100.4502744.91191e-06
110.7145297.79460
120.8434829.20130
130.6516437.10860
140.3475853.79170.000118
150.1146041.25020.106843
16-0.013019-0.1420.443651
17-0.066821-0.72890.233739
18-0.100071-1.09160.138598
19-0.083737-0.91350.181422
20-0.039779-0.43390.332561
210.0635920.69370.24461
220.255062.78240.003139
230.4807435.24430
240.5739836.26140
250.3873794.22582.3e-05
260.1100881.20090.116085
27-0.094665-1.03270.151924
28-0.206351-2.2510.01311
29-0.253547-2.76590.003292
30-0.282548-3.08220.001277
31-0.264162-2.88170.002347
32-0.222008-2.42180.008476
33-0.126156-1.37620.085673
340.0474140.51720.30298
350.243012.65090.00456
360.3138973.42420.000423
370.1422311.55160.061711
38-0.099164-1.08180.140775
39-0.265847-2.90010.002222
40-0.349122-3.80850.000111
41-0.375939-4.1013.8e-05
42-0.389831-4.25262.1e-05
43-0.364994-3.98165.9e-05
44-0.324663-3.54170.000284
45-0.235443-2.56840.005727
46-0.081473-0.88880.18796
470.0875420.9550.170765
480.144971.58140.058216
490.0041340.04510.482055
50-0.189595-2.06820.020392
51-0.315012-3.43640.000406
52-0.372769-4.06644.3e-05
53-0.385258-4.20272.6e-05
54-0.385134-4.20132.6e-05
55-0.354495-3.86719e-05
56-0.313718-3.42230.000426
57-0.236686-2.58190.005519
58-0.106928-1.16650.122882
590.0359360.3920.347875
600.0864270.94280.173844


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8182288.92580
2-0.502513-5.48180
30.2041342.22680.01392
4-0.01233-0.13450.446615
5-0.010778-0.11760.453303
6-0.025732-0.28070.389715
70.2157782.35390.010109
8-0.056757-0.61910.268503
90.3966174.32661.6e-05
100.3871394.22322.4e-05
110.5161055.630
12-0.028229-0.30790.379331
13-0.658696-7.18550
140.214052.3350.010609
15-0.176785-1.92850.028088
16-0.224225-2.4460.007954
170.0521130.56850.285389
18-0.109631-1.19590.11705
19-0.182112-1.98660.024632
20-0.102924-1.12280.131898
21-0.037188-0.40570.342857
22-0.064635-0.70510.241067
23-0.101773-1.11020.134572
240.0192420.20990.417051
250.0117540.12820.449094
26-0.020384-0.22240.412206
270.0541440.59060.277939
28-0.00152-0.01660.493399
29-0.060741-0.66260.254431
300.0482780.52660.29971
310.038330.41810.338302
32-0.102233-1.11520.133499
330.0563750.6150.269871
34-0.060454-0.65950.255432
35-0.048744-0.53170.297952
36-0.002646-0.02890.488509
37-0.01302-0.1420.443647
380.0035590.03880.484548
390.0292720.31930.375024
400.0339950.37080.355707
410.0713460.77830.218969
42-0.021854-0.23840.405992
430.0226130.24670.402791
44-0.034342-0.37460.354303
450.018120.19770.421821
46-0.122164-1.33270.092596
470.0608820.66410.253942
48-0.034001-0.37090.355683
490.1404941.53260.064014
50-0.107732-1.17520.121128
510.0446870.48750.313409
52-0.032276-0.35210.362697
53-0.039008-0.42550.335612
540.0323060.35240.362573
550.0301170.32850.371542
56-0.023902-0.26070.397373
57-0.085782-0.93580.175643
58-0.023974-0.26150.39707
590.0181410.19790.421731
60-0.050783-0.5540.290318
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229700993e0ldwct6hhtoxjo/1qbv41229700902.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229700993e0ldwct6hhtoxjo/1qbv41229700902.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229700993e0ldwct6hhtoxjo/2lx3q1229700902.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229700993e0ldwct6hhtoxjo/2lx3q1229700902.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
 
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 (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='lags',ylab='ACF')
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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