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(Partial) Autocorrelation voor het aantal faillissementen in het Vlaamse Gewest

*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, 12 Dec 2008 02:41:51 -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/12/t1229074964h8825oy7drap99w.htm/, Retrieved Fri, 12 Dec 2008 10:42:44 +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/12/t1229074964h8825oy7drap99w.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},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
293 301 362 330 328 405 232 159 336 361 329 339 290 328 375 294 340 364 248 145 380 305 291 319 334 318 362 296 300 342 215 185 343 333 316 252 320 324 343 295 301 367 196 182 342 361 334 330 345 323 366 323 316 358 235 169 430 409 407 341 326 374 364 349 300 385 304 196 443 414 325 388 356 386 444 387 327 448 225 182 460 411 342 361 377 331 428 340 352 461 221 198 422 329 320 375 364 351 380 319 322 386 221 187 344 342 365 313 356 337 389 326 343 357 220 218 391 425 332 298
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1199881.31440.095609
2-0.274193-3.00360.001624
30.1569361.71920.044083
40.0078280.08570.465905
5-0.065144-0.71360.238425
60.1215381.33140.092794
7-0.051346-0.56250.287425
80.0283990.31110.378135
90.1656321.81440.036057
10-0.242999-2.66190.004417
110.1350331.47920.070851
120.7820158.56650
130.0494530.54170.294503
14-0.261568-2.86530.00246
150.141241.54720.062223
160.00120.01310.494766
17-0.085836-0.94030.174479
180.0678470.74320.229397
19-0.089153-0.97660.16536
200.0048180.05280.478997
210.1098331.20320.115642
22-0.26036-2.85210.002558
230.0843390.92390.178699
240.626646.86450
250.0140390.15380.439016
26-0.285248-3.12470.001116
270.0383890.42050.337423
28-0.016442-0.18010.428683
29-0.104209-1.14160.127956
300.0108790.11920.452668
31-0.091813-1.00580.158277
32-0.037746-0.41350.339994
330.0107030.11720.453433
34-0.269722-2.95470.001884
350.0410280.44940.326962
360.5122255.61110
37-0.019257-0.2110.416641
38-0.284988-3.12190.001126
39-0.009274-0.10160.459626
40-0.049339-0.54050.294933
41-0.13098-1.43480.07697
42-0.013731-0.15040.440346
43-0.070457-0.77180.22087
44-0.075216-0.8240.205801
45-0.023242-0.25460.399731
46-0.252874-2.77010.003248
470.004380.0480.480907
480.4179854.57886e-06
49-0.031612-0.34630.364867
50-0.260081-2.8490.002581
51-0.004581-0.05020.48003
52-0.038017-0.41650.33891
53-0.123454-1.35240.0894
54-0.023105-0.25310.400311
55-0.075446-0.82650.205089
56-0.080796-0.88510.188943
57-0.019252-0.21090.416665
58-0.185396-2.03090.022237
590.0185470.20320.419671
600.3608533.95296.5e-05


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1199881.31440.095609
2-0.292805-3.20750.000858
30.2603512.8520.002559
4-0.179849-1.97020.025562
50.1214831.33080.092893
60.0204880.22440.411401
7-0.070692-0.77440.220112
80.1553461.70170.045698
90.0246440.270.393826
10-0.24598-2.69460.004029
110.4223624.62675e-06
120.6405347.01670
13-0.066239-0.72560.234744
140.0215510.23610.406885
15-0.017332-0.18990.424871
160.0196580.21530.414931
17-0.063577-0.69650.243745
18-0.117087-1.28260.101048
19-0.110062-1.20570.115158
20-0.105383-1.15440.125312
21-0.126612-1.3870.084011
22-0.14784-1.61950.053981
23-0.137318-1.50420.067573
240.0296170.32440.373087
250.0242050.26510.395675
26-0.097809-1.07140.14306
27-0.186325-2.04110.021718
280.0519460.5690.285198
29-0.020516-0.22470.41128
300.0150020.16430.434872
310.0506850.55520.289885
32-0.057883-0.63410.26362
33-0.071027-0.77810.219033
340.0071320.07810.46893
35-0.033383-0.36570.357619
360.0797140.87320.192143
37-0.036541-0.40030.344828
380.1060651.16190.123794
39-0.01204-0.13190.447647
40-0.062289-0.68230.248168
41-0.007433-0.08140.46762
420.0641790.7030.241694
430.0599320.65650.256373
44-0.047098-0.51590.303423
450.0357010.39110.348214
46-0.044828-0.49110.312138
47-0.025865-0.28330.388704
480.0010210.01120.495549
49-0.056923-0.62360.267052
500.0400480.43870.330834
510.0329180.36060.359516
520.0094130.10310.459022
53-0.003113-0.03410.486426
54-0.066837-0.73220.232749
55-0.010819-0.11850.452929
56-0.009135-0.10010.460228
57-0.00061-0.00670.497339
580.1005921.10190.136348
59-0.013478-0.14760.441435
600.0014830.01620.493534
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229074964h8825oy7drap99w/1t3rg1229074905.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229074964h8825oy7drap99w/1t3rg1229074905.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229074964h8825oy7drap99w/2edu51229074905.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229074964h8825oy7drap99w/2edu51229074905.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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