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parial autocorrelation rent D0 d2

*Unverified author*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Thu, 17 Dec 2009 15:32:33 -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/17/t12610892039oqsfc3f8akr8cd.htm/, Retrieved Thu, 17 Dec 2009 23:33:25 +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/17/t12610892039oqsfc3f8akr8cd.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 «
3.25 3.25 3.25 3.25 3.25 3.25 2.85 2.75 2.75 2.55 2.5 2.5 2.1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2.21 2.25 2.25 2.45 2.5 2.5 2.64 2.75 2.93 3 3.17 3.25 3.39 3.5 3.5 3.65 3.75 3.75 3.9 4 4 4 4 4 4 4 4 4 4 4 4 4.18 4.25 4.25 3.97 3.42 2.75 2.31 2 1.66 1.31 1.09 1 1 1
 
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
1-0.202411-1.86610.032736
2-0.212623-1.96030.026619
30.2446012.25510.013348
4-0.187008-1.72410.04416
5-0.135108-1.24560.108161
60.2275242.09770.019452
7-0.114348-1.05420.147381
8-0.091328-0.8420.201076
9-0.051817-0.47770.317036
100.0349070.32180.374187
11-0.071488-0.65910.25581
120.0822870.75860.225081
130.0329820.30410.380906
14-0.086724-0.79960.2131
150.0996150.91840.180503
160.0238570.220.413217
17-0.106144-0.97860.165277
180.0323960.29870.382959
190.0358280.33030.370987
20-0.038841-0.35810.360578
210.0019250.01780.49294
22-0.008371-0.07720.469332
230.025950.23920.405745
24-0.033065-0.30480.380613
250.0367490.33880.367796
26-0.026034-0.240.405446
27-0.015152-0.13970.444618
280.0189180.17440.430975
290.000670.00620.497544
30-0.119371-1.10050.137102
310.1425581.31430.096137
320.0380880.35120.363171
33-0.184915-1.70480.045939
340.110331.01720.155975
350.1185331.09280.138779
36-0.273732-2.52370.006737
370.1167751.07660.142349
380.0621970.57340.283936
39-0.076427-0.70460.241485
40-0.002009-0.01850.492633
410.0720740.66450.254087
42-0.048133-0.44380.329169
430.0036830.0340.486495
440.048970.45150.326395
45-0.035158-0.32410.373313
46-0.049389-0.45530.325012
470.1448181.33520.092695
48-0.143563-1.32360.094595
49-0.011301-0.10420.458633
500.1372841.26570.104539
51-0.10673-0.9840.163953
52000.5
530.083710.77180.221196
54-0.071154-0.6560.256797
55-0.008371-0.07720.469332
560.0334840.30870.37915
57000.5
58000.5
590.0150680.13890.444922
600.0359950.33190.370406


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.202411-1.86610.032736
2-0.264427-2.43790.008428
30.1532111.41250.080721
4-0.173576-1.60030.056622
5-0.137641-1.2690.103955
60.0755490.69650.244
7-0.063628-0.58660.279505
8-0.060715-0.55980.288558
9-0.244233-2.25170.013459
100.00640.0590.476544
11-0.125415-1.15630.125405
120.0350510.32320.373685
13-0.051607-0.47580.317722
14-0.075363-0.69480.244533
150.0819540.75560.225995
16-0.034551-0.31850.375428
17-0.036404-0.33560.368989
18-0.12313-1.13520.129741
190.0269990.24890.402013
20-0.004726-0.04360.482673
21-0.035678-0.32890.371506
22-0.066951-0.61730.269358
230.0314430.28990.386302
240.0028190.0260.489661
25-0.000456-0.00420.498328
26-0.075046-0.69190.245445
27-0.026059-0.24030.405355
28-0.001812-0.01670.493357
29-0.009066-0.08360.466793
30-0.172233-1.58790.05801
310.0701270.64650.259835
320.0782220.72120.236392
33-0.14189-1.30820.097172
34-0.010572-0.09750.461292
350.0558980.51540.303822
36-0.126953-1.17040.122546
37-0.048365-0.44590.328399
38-0.100896-0.93020.177447
390.0848950.78270.217992
40-0.096142-0.88640.188955
41-0.006006-0.05540.477987
42-0.02709-0.24980.401689
430.0023910.0220.491233
440.0076140.07020.472102
45-0.100207-0.92390.179087
46-0.040569-0.3740.354656
470.0435830.40180.344413
48-0.07732-0.71290.238944
49-0.038474-0.35470.361843
50-0.015685-0.14460.442682
510.0152490.14060.444263
52-0.001233-0.01140.495477
53-0.045186-0.41660.339012
54-0.045643-0.42080.337479
55-0.033255-0.30660.379952
56-0.001389-0.01280.494905
57-0.035734-0.32940.371314
58-0.028892-0.26640.395299
590.0172790.15930.436903
600.0511970.4720.319064
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/17/t12610892039oqsfc3f8akr8cd/1xhki1261089151.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/17/t12610892039oqsfc3f8akr8cd/1xhki1261089151.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/17/t12610892039oqsfc3f8akr8cd/2cmb21261089151.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/17/t12610892039oqsfc3f8akr8cd/2cmb21261089151.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; 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 (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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