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KDGP2W21

*Unverified author*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Sun, 06 Dec 2009 07:23:34 -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/06/t1260109477mzdzfajnksxttqn.htm/, Retrieved Sun, 06 Dec 2009 15:24:39 +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/06/t1260109477mzdzfajnksxttqn.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:
parameter "degree of non-seasonal differencing" "1" maandelijkse bezoekers VS
 
Dataseries X:
» Textbox « » Textfile « » CSV «
2357402 2199181 2603060 2629720 2638792 2717481 3810804 3871664 2998364 2923432 2712359 2996099 2395029 2483862 3120231 3360606 3177203 3062783 4242509 4026394 3192481 3118695 2782482 3209833 2630190 2592882 3785309 3231539 3421369 3312134 4647303 4289177 3463853 3304422 3006121 3464238 2921118 2624018 3500718 3939351 3467672 3343628 4852445 4597807 3653145 3572079 3334861 3695369 3075704 2852998 3942704 4004560 3822145 3760085 5267816 5271333 4144142 4109749 3896808 4211074 3402318 3279817 4706628 4079499 4344530 4048625 5394915 5611967 4145481 4025610 3552218 3910443
 
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
1-0.148497-1.25130.107473
2-0.342951-2.88980.002555
3-0.012312-0.10370.458833
40.24382.05430.021815
50.11380.95890.170433
6-0.68432-5.76620
70.090040.75870.225275
80.2536982.13770.017993
9-0.001841-0.01550.493832
10-0.285155-2.40280.009444
11-0.085407-0.71970.23705
120.7373016.21260
13-0.059352-0.50010.309271
14-0.323626-2.72690.004024
150.0147630.12440.450678
160.191961.61750.055104
170.0706060.59490.276889
18-0.528578-4.45391.5e-05
190.0619920.52240.301526
200.2175311.83290.035502
21-0.030237-0.25480.399813
22-0.214052-1.80360.037765
23-0.074933-0.63140.264904
240.5756154.85024e-06
25-0.033047-0.27850.390733
26-0.245582-2.06930.021079
270.0019130.01610.493593
280.1471331.23980.109573
290.0661690.55750.289454
30-0.393346-3.31440.000724
310.0195490.16470.434816
320.1662881.40120.08276
33-0.012521-0.10550.458137
34-0.142848-1.20370.116359
35-0.098782-0.83230.204001
360.4503053.79430.000154
37-0.023554-0.19850.421622
38-0.166233-1.40070.082828
39-0.000458-0.00390.498467
400.0659950.55610.289951
410.086370.72780.234574
42-0.295379-2.48890.00758
430.0347850.29310.385148
440.1070910.90240.184958
45-0.037328-0.31450.377021
46-0.078127-0.65830.256235
47-0.032081-0.27030.393849
480.2629352.21550.014966


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.148497-1.25130.107473
2-0.373233-3.14490.001213
3-0.16356-1.37820.086238
40.0937630.79010.216062
50.1680731.41620.080544
6-0.632921-5.33311e-06
7-0.113486-0.95620.171096
8-0.223623-1.88430.03181
9-0.152567-1.28560.101388
10-0.392787-3.30970.000735
11-0.338418-2.85160.002847
120.2457212.07050.021022
130.1143050.96310.169371
140.0047170.03970.484205
150.1333811.12390.132423
16-0.073589-0.62010.268598
17-0.066194-0.55780.289381
180.0813120.68510.247741
190.1425471.20110.116847
20-0.021617-0.18210.427993
210.0198860.16760.433701
22-0.04807-0.4050.343331
23-0.149155-1.25680.106471
24-0.035391-0.29820.383208
25-0.030653-0.25830.398466
260.0135450.11410.454728
27-0.062956-0.53050.298717
28-0.075482-0.6360.263403
29-0.060488-0.50970.305928
300.0379770.320.374955
31-0.037431-0.31540.376692
320.0109750.09250.463291
330.0273890.23080.409075
340.0747550.62990.265392
35-0.063922-0.53860.295918
360.1081260.91110.182667
37-0.093678-0.78930.21627
380.0485280.40890.341921
390.003870.03260.487039
40-0.028467-0.23990.405563
41-0.097792-0.8240.206347
420.0144650.12190.451667
43-0.009236-0.07780.469092
440.0614720.5180.303044
45-0.093248-0.78570.217322
46-0.010161-0.08560.466005
470.1568891.3220.095211
48-0.089579-0.75480.226432
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/06/t1260109477mzdzfajnksxttqn/13pay1260109412.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/06/t1260109477mzdzfajnksxttqn/13pay1260109412.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/06/t1260109477mzdzfajnksxttqn/2szt91260109412.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/06/t1260109477mzdzfajnksxttqn/2szt91260109412.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; 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')
 




Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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