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Autocorrelatie - Goudkoers - Steffi Heivers

*Unverified author*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Wed, 28 Apr 2010 16:02:27 +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/Apr/28/t12724706271s6h8fzy21liwc7.htm/, Retrieved Wed, 28 Apr 2010 18:03:47 +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/Apr/28/t12724706271s6h8fzy21liwc7.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:
KDGP2W21
 
Dataseries X:
» Textbox « » Textfile « » CSV «
25204 24977 24320 22680 22052 21467 21383 21777 21928 21814 22937 23595 20830 19650 19195 19644 18483 18079 19178 18391 18441 18584 20108 20148 19394 17745 17696 17032 16438 15683 15594 15713 15937 16171 15928 16348 15579 15305 15648 14954 15137 15839 16050 15168 17064 16005 14886 14931 14544 13812 13031 12574 11964 11451 11346 11353 10702 10646 10556 10463 10407 10625 10872 10805 10653 10574 10431 10383 10296 10872 10635 10297 10570
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9437988.06380
20.8844497.55670
30.8323217.11140
40.7890796.74190
50.743626.35350
60.706486.03620
70.6743095.76130
80.6387915.45780
90.6027455.14991e-06
100.5646924.82474e-06
110.5188594.43311.6e-05
120.4617813.94559.1e-05
130.4178213.56990.000318
140.3771423.22230.000951
150.3394632.90040.002461
160.299412.55820.006299
170.2670072.28130.012724
180.2403142.05320.021816
190.2063571.76310.041033
200.1820021.5550.062133
210.1569891.34130.091988
220.1311631.12070.133054
230.0904880.77310.220972
240.0503650.43030.334115
250.0147230.12580.450121
26-0.010645-0.0910.463889
27-0.038756-0.33110.370748
28-0.059469-0.50810.306457
29-0.069304-0.59210.277795
30-0.081435-0.69580.244387
31-0.088949-0.760.224857
32-0.099782-0.85250.198352
33-0.112347-0.95990.170139
34-0.131513-1.12360.132423
35-0.150784-1.28830.100856
36-0.173069-1.47870.071761
37-0.190252-1.62550.054182
38-0.205368-1.75470.041756
39-0.22428-1.91630.029624
40-0.237591-2.030.023002
41-0.255296-2.18130.016193
42-0.278031-2.37550.010076
43-0.303-2.58880.005808
44-0.323453-2.76360.003616
45-0.355512-3.03750.001654
46-0.378534-3.23420.000917
47-0.39274-3.35560.00063
48-0.409724-3.50070.000398


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9437988.06380
2-0.057716-0.49310.311703
30.0355850.3040.380981
40.0493650.42180.337215
5-0.045565-0.38930.34909
60.0613010.52380.301018
70.0221310.18910.425275
8-0.047552-0.40630.34286
9-0.006696-0.05720.477266
10-0.041428-0.3540.362193
11-0.095453-0.81560.208705
12-0.123711-1.0570.147001
130.0779130.66570.253853
14-0.031469-0.26890.394393
15-0.003689-0.03150.48747
16-0.039684-0.33910.36777
170.0231670.19790.421823
180.0363980.3110.378348
19-0.077147-0.65910.255939
200.0867460.74120.230488
21-0.030851-0.26360.39642
22-0.016229-0.13870.445049
23-0.143374-1.2250.112259
24-0.057805-0.49390.311434
250.006930.05920.476473
260.0467760.39970.345289
27-0.058468-0.49950.309448
280.0199080.17010.432703
290.084350.72070.236702
30-0.031927-0.27280.392894
310.0381270.32580.372771
32-0.015317-0.13090.44812
33-0.016485-0.14090.444187
34-0.024686-0.21090.416769
35-0.075213-0.64260.261241
36-0.081416-0.69560.244439
370.0154770.13220.44758
38-0.016828-0.14380.443037
39-0.108389-0.92610.178729
400.0184770.15790.4375
41-0.052244-0.44640.328326
42-0.090274-0.77130.221508
43-0.021218-0.18130.428323
44-0.013147-0.11230.455436
45-0.097633-0.83420.203452
460.0556680.47560.317879
470.0140620.12010.452347
48-0.105804-0.9040.184487
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Apr/28/t12724706271s6h8fzy21liwc7/1bx2y1272470544.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Apr/28/t12724706271s6h8fzy21liwc7/1bx2y1272470544.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Apr/28/t12724706271s6h8fzy21liwc7/2bx2y1272470544.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Apr/28/t12724706271s6h8fzy21liwc7/2bx2y1272470544.ps (open in new window)


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





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