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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: Thu, 11 Dec 2008 08:23:01 -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/11/t1229009020d68bgqamfoj5bjk.htm/, Retrieved Thu, 11 Dec 2008 15:23:42 +0000
 
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/11/t1229009020d68bgqamfoj5bjk.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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.518573-5.36420
20.0293480.30360.381018
30.0653020.67550.25041
4-0.154446-1.59760.056541
50.0354750.3670.357189
60.0539650.55820.28893
7-0.006268-0.06480.474213
8-0.00666-0.06890.472601
90.0635450.65730.256196
10-0.124061-1.28330.101079
110.243352.51720.006655
12-0.261152-2.70140.004015
130.0100720.10420.458608
140.0548060.56690.28598
150.1026741.06210.145297
16-0.128732-1.33160.092909
170.0619380.64070.261545
180.046990.48610.313957
19-0.16347-1.69090.046879
200.1391641.43950.07646
210.0081050.08380.466673
22-0.131009-1.35520.089109
230.1797671.85950.03285
24-0.166057-1.71770.044371
250.0702280.72640.234576
260.043930.45440.325226
27-0.091179-0.94320.173861
280.0708610.7330.232584
29-0.017794-0.18410.427158
30-0.006681-0.06910.472515
31-0.043072-0.44550.328413
320.0788590.81570.208234
33-0.119992-1.24120.108621
340.1521661.5740.059218
35-0.021961-0.22720.410363
36-0.087649-0.90660.183316
370.0150140.15530.438436
380.0672080.69520.244218
39-0.130009-1.34480.090763
400.0886740.91730.180536
410.0534970.55340.290581
42-0.153559-1.58840.05757
430.1899751.96510.025996
44-0.085367-0.8830.189597
450.040360.41750.338578
46-0.069296-0.71680.237528
47-0.052881-0.5470.292755
480.0606810.62770.265772
490.0190110.19670.422237
500.0198730.20560.418758
51-0.001381-0.01430.494316
52-0.024982-0.25840.398292
530.0047250.04890.480554
54-0.053877-0.55730.289241
550.0762010.78820.216153
56-0.029459-0.30470.380582
57-0.046754-0.48360.31482
580.0781460.80830.210343
591.8e-052e-040.499925
60-0.069551-0.71940.23672


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.518573-5.36420
2-0.327692-3.38970.00049
3-0.12937-1.33820.091832
4-0.251806-2.60470.005251
5-0.282467-2.92190.002123
6-0.204959-2.12010.018154
7-0.137962-1.42710.078233
8-0.149391-1.54530.062612
9-0.043294-0.44780.327589
10-0.151141-1.56340.060454
110.231152.3910.009274
120.0514280.5320.297924
13-0.10316-1.06710.144164
14-0.16909-1.74910.041572
150.1537461.59040.057352
16-0.000184-0.00190.499244
17-0.110897-1.14710.126945
180.002210.02290.490902
19-0.056201-0.58140.281113
20-0.039453-0.40810.342007
210.0936110.96830.167534
22-0.144343-1.49310.069177
230.1677491.73520.042791
24-0.01079-0.11160.455672
25-0.03218-0.33290.369943
26-0.103828-1.0740.142618
270.0449240.46470.321545
280.0477820.49430.311069
29-0.071557-0.74020.230404
30-0.002882-0.02980.488136
31-0.082387-0.85220.197999
32-0.05623-0.58170.281013
33-0.105109-1.08730.139684
34-0.045291-0.46850.320193
350.1733651.79330.037875
36-0.014303-0.14790.441331
37-0.111058-1.14880.126602
38-0.012931-0.13380.446922
39-0.034635-0.35830.360425
40-0.05455-0.56430.286875
41-0.108153-1.11870.132878
42-0.127684-1.32080.094698
43-0.021148-0.21880.413628
440.0311210.32190.37407
450.1309441.35450.089216
46-0.007529-0.07790.469033
470.0607350.62820.26559
480.0136670.14140.443919
49-0.129668-1.34130.091331
50-0.007844-0.08110.467743
510.0245170.25360.400145
52-0.089763-0.92850.177614
53-0.040668-0.42070.33742
54-0.119491-1.2360.109578
55-0.052599-0.54410.293758
56-0.009108-0.09420.462558
570.0305830.31640.376176
58-0.073024-0.75540.225845
590.0613260.63440.263601
60-0.061901-0.64030.261671
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229009020d68bgqamfoj5bjk/1v52y1229008979.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229009020d68bgqamfoj5bjk/1v52y1229008979.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229009020d68bgqamfoj5bjk/25g1y1229008979.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229009020d68bgqamfoj5bjk/25g1y1229008979.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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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Error 001_3: History of computation (impact.txt) is not saved due to a technical problem. We are sorry for this inconveniance and will correct it A.S.A.P.