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TIJDREEK A - Stap 21

*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, 19 Aug 2010 16:00:48 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Aug/19/t12822336534aybpu0706igp2m.htm/, Retrieved Thu, 19 Aug 2010 18:00:55 +0200
 
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/2010/Aug/19/t12822336534aybpu0706igp2m.htm/},
    year = {2010},
}
@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 = {2010},
    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:
Van Boxel Dieter
 
Dataseries X:
» Textbox « » Textfile « » CSV «
356 355 354 352 372 371 356 346 347 347 348 350 353 350 343 346 373 363 349 350 353 356 355 346 349 348 342 342 379 375 363 361 363 373 367 360 358 367 357 346 386 383 367 354 363 370 361 354 363 366 353 351 389 385 364 348 347 352 342 338 343 354 329 320 353 345 324 310 314 313 310 301 294 296 274 269 292 287 271 256 260 265 263 256 246 245 220 224 240 238 222 203 209 214 216 214 206 196 169 177 193 183 164 142 141 137 140 146 136 124 105 114 135 123 100 74 64 57 62 64
 
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
10.96313710.00920
20.9301059.66590
30.9027399.38150
40.8725989.06830
50.8405658.73540
60.8209238.53130
70.8089248.40660
80.7897388.20720
90.7680727.9820
100.7429377.72080
110.715477.43540
120.6893577.1640
130.6648866.90970
140.6296736.54380
150.5949366.18280
160.56665.88830
170.5374155.5850
180.5044615.24250
190.4734324.92012e-06
200.4457884.63285e-06
210.416434.32771.7e-05
220.3857624.0095.6e-05
230.3564473.70430.000168
240.334343.47460.000369
250.3139523.26270.000739
260.2911563.02580.00155
270.261912.72180.003785
280.2417852.51270.006729
290.219652.28270.012204
300.1948472.02490.022672
310.1688711.7550.041051
320.1450971.50790.067251
330.1207991.25540.106025
340.0855110.88870.188083
350.0571630.59410.276859
360.0324220.33690.36841
370.0098640.10250.459272
38-0.012268-0.12750.449394
39-0.030862-0.32070.374518
40-0.05617-0.58370.280306
41-0.082363-0.85590.196963
42-0.109974-1.14290.127807
43-0.143241-1.48860.069752
44-0.17692-1.83860.03436
45-0.19807-2.05840.020979
46-0.222577-2.31310.011306
47-0.249903-2.59710.005356
48-0.270851-2.81480.002901


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.96313710.00920
20.0341450.35480.361699
30.0639410.66450.253896
4-0.044788-0.46550.321271
5-0.039858-0.41420.339769
60.1475911.53380.064
70.1118211.16210.123883
8-0.072029-0.74850.227878
9-0.051053-0.53060.298409
10-0.091314-0.9490.172378
11-0.031246-0.32470.373011
120.038330.39830.345586
130.0025760.02680.489348
14-0.194207-2.01830.023022
15-0.062463-0.64910.258814
160.0362220.37640.353666
170.0117670.12230.45145
18-0.037082-0.38540.35036
19-0.06119-0.63590.263091
20-0.030944-0.32160.374196
210.0098750.10260.459224
220.0066450.06910.472535
23-0.00632-0.06570.473876
240.0728110.75670.225445
250.0186130.19340.423493
26-0.034461-0.35810.360473
27-0.093425-0.97090.166883
280.1091351.13420.129618
29-0.021297-0.22130.412629
30-0.015029-0.15620.438087
31-0.061427-0.63840.262293
32-0.052325-0.54380.293858
33-0.027928-0.29020.386094
34-0.152198-1.58170.058323
350.0456270.47420.318169
360.0136970.14230.443536
37-0.016644-0.1730.431501
38-0.037447-0.38920.348963
390.0077730.08080.467882
40-0.086992-0.9040.183992
41-0.028824-0.29960.382547
42-0.052124-0.54170.294576
43-0.084954-0.88290.189635
44-0.040195-0.41770.338491
450.1134171.17870.120562
46-0.091955-0.95560.170699
47-0.003512-0.03650.485475
480.014410.14970.440621
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Aug/19/t12822336534aybpu0706igp2m/10dff1282233646.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Aug/19/t12822336534aybpu0706igp2m/10dff1282233646.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Aug/19/t12822336534aybpu0706igp2m/20dff1282233646.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Aug/19/t12822336534aybpu0706igp2m/20dff1282233646.ps (open in new window)


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