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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 02:46:16 -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/t1229075211nwli8wnhvrxyues.htm/, Retrieved Fri, 12 Dec 2008 10:46:51 +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/t1229075211nwli8wnhvrxyues.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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0843540.87660.191315
20.1161171.20670.115089
30.1073761.11590.133473
4-0.026661-0.27710.391127
50.1215951.26370.104538
60.1994092.07230.020308
70.1771641.84110.034173
80.1712391.77960.03898
90.1778291.84810.033665
100.0650180.67570.250342
110.1770711.84020.034245
12-0.154658-1.60730.05546
13-0.012916-0.13420.446735
140.1211311.25880.105404
150.1510931.57020.059646
16-0.016969-0.17630.430177
170.0568650.5910.277891
180.0193340.20090.420566
19-0.113359-1.17810.12068
200.0606990.63080.264753
21-0.021385-0.22220.412273
22-0.119275-1.23950.108915
230.0303330.31520.376597
24-0.155883-1.620.054076
25-0.033343-0.34650.364817
26-0.042814-0.44490.328627
27-0.140593-1.46110.073448
28-0.065841-0.68420.247646
29-0.114288-1.18770.118776
30-0.13173-1.3690.086923
31-0.136456-1.41810.079522
32-0.060417-0.62790.265707
33-0.137037-1.42410.078646
340.0104240.10830.456967
35-0.125424-1.30340.097598
36-0.21016-2.1840.015561
37-0.142083-1.47660.071351
38-0.097193-1.01010.157362
39-0.176775-1.83710.034472
40-0.016048-0.16680.43393
41-0.021628-0.22480.411293
42-0.133573-1.38810.083977
430.0536930.5580.289003
44-0.112522-1.16940.122417
45-0.117853-1.22480.111665
46-0.193441-2.01030.023446
47-0.149444-1.55310.061667
48-0.00874-0.09080.463898
490.0219760.22840.409891
500.0050960.0530.478933
51-0.039759-0.41320.340146
52-0.080196-0.83340.203223
53-0.074719-0.77650.219574
54-0.071444-0.74250.229708
550.0268650.27920.390319
56-0.020741-0.21550.414873
57-0.010013-0.10410.458656
580.0826610.8590.196112
590.0357070.37110.355651
60-0.015091-0.15680.437837


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0843540.87660.191315
20.1097821.14090.12822
30.0911350.94710.17285
4-0.054783-0.56930.285162
50.1087071.12970.130549
60.1898581.97310.025522
70.1474911.53280.064128
80.1031651.07210.143027
90.1293831.34460.090788
100.0249880.25970.397801
110.1324111.37610.085825
12-0.261377-2.71630.003845
13-0.111343-1.15710.12489
140.0410060.42620.335423
150.1280571.33080.093028
16-0.199273-2.07090.020376
17-0.058495-0.60790.272266
180.0554810.57660.282713
19-0.058849-0.61160.271051
200.0023060.0240.490462
21-0.008335-0.08660.465566
22-0.147627-1.53420.063954
230.091940.95550.170736
24-0.224979-2.3380.010613
25-0.054324-0.56460.286774
26-0.034322-0.35670.361012
270.0466490.48480.314405
28-0.103308-1.07360.142696
29-0.111906-1.1630.123704
300.0108980.11330.455018
31-0.05725-0.5950.276557
320.0253570.26350.396326
330.0087330.09080.463929
340.0745770.7750.220008
350.0123970.12880.448865
36-0.212081-2.2040.014823
37-0.048833-0.50750.306424
380.0508320.52830.2992
39-0.039757-0.41320.340153
40-0.015265-0.15860.437124
410.0041330.04290.482912
420.0621080.64540.260004
430.1040271.08110.141036
440.0137350.14270.443382
45-0.037692-0.39170.348024
46-0.149537-1.5540.061551
47-0.034129-0.35470.361762
48-0.100955-1.04920.148225
49-0.05761-0.59870.275314
500.0777980.80850.21029
51-0.043391-0.45090.326472
52-0.080115-0.83260.203459
530.0381230.39620.346375
54-0.009744-0.10130.459765
550.0793360.82450.205742
560.0274260.2850.388087
57-0.00668-0.06940.472391
58-0.054913-0.57070.284704
590.0451710.46940.319854
60-0.082021-0.85240.197944
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229075211nwli8wnhvrxyues/1md4j1229075168.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229075211nwli8wnhvrxyues/1md4j1229075168.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229075211nwli8wnhvrxyues/2s49q1229075168.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229075211nwli8wnhvrxyues/2s49q1229075168.ps (open in new window)


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