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Evolutie prijzen korte sigaretten (Opgave 6bis, stap 2)

*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, 18 Nov 2010 17:56:48 +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/Nov/18/t1290103005mvtr2ueqngzpu0i.htm/, Retrieved Thu, 18 Nov 2010 18:56:47 +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/2010/Nov/18/t1290103005mvtr2ueqngzpu0i.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:
KDGP2W12
 
Dataseries X:
» Textbox « » Textfile « » CSV «
4.23 4.38 4.43 4.44 4.44 4.44 4.44 4.44 4.45 4.45 4.45 4.45 4.45 4.45 4.45 4.45 4.46 4.46 4.46 4.48 4.58 4.67 4.68 4.68 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.73 4.78 4.79 4.79 4.8 4.8 4.81 5.16 5.26 5.29 5.29 5.29 5.3 5.3 5.3 5.3 5.3 5.3 5.3 5.3 5.35 5.44 5.47 5.47 5.48 5.48 5.48 5.48 5.48 5.48 5.48 5.5 5.55 5.57 5.58 5.58 5.58 5.59 5.59 5.59 5.55
 
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'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2898932.44270.008534
2-0.017566-0.1480.441376
3-0.090298-0.76090.224628
4-0.099834-0.84120.201527
5-0.077115-0.64980.258964
6-0.022224-0.18730.425995
7-0.016247-0.13690.445748
8-0.10293-0.86730.194349
9-0.115087-0.96970.167734
10-0.084487-0.71190.239429
11-0.034192-0.28810.387053
12-0.01607-0.13540.446338
130.0514610.43360.332939
140.0960110.8090.210607
15-0.04788-0.40340.343917
16-0.094759-0.79850.213634
170.0910410.76710.222775
180.1614451.36040.08901
190.0866650.73030.233819
200.0182210.15350.439206
21-0.064755-0.54560.293513
22-0.070269-0.59210.277833
23-0.06651-0.56040.288479
24-0.032382-0.27290.392879
250.0012530.01060.495804
26-0.067952-0.57260.284372
27-0.092344-0.77810.219547
28-0.110416-0.93040.177663
29-0.094098-0.79290.215243
300.006180.05210.479308
310.0216810.18270.427783
32-0.036106-0.30420.380919
33-0.146417-1.23370.110686
34-0.051843-0.43680.331777
35-0.036755-0.30970.378846
360.0503090.42390.336456
370.2647542.23090.014425
380.0577060.48620.314146
39-0.008366-0.07050.471999
40-0.025937-0.21850.413814
41-0.00067-0.00560.497757
420.0277940.23420.407753
430.0245780.20710.418262
440.0059320.050.480139
45-0.014439-0.12170.451754
46-0.023319-0.19650.422395
47-0.021858-0.18420.427201
48-0.019328-0.16290.435545


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2898932.44270.008534
2-0.110926-0.93470.176561
3-0.058014-0.48880.313234
4-0.06226-0.52460.300743
5-0.041685-0.35120.363222
6-0.001026-0.00860.496565
7-0.029204-0.24610.403168
8-0.116067-0.9780.165698
9-0.07034-0.59270.277635
10-0.055394-0.46680.321051
11-0.027097-0.22830.410024
12-0.042255-0.3560.361431
130.031560.26590.395531
140.0478920.40350.343881
15-0.119599-1.00780.158497
16-0.065667-0.55330.290892
170.1396171.17640.121675
180.0838230.70630.241155
19-0.003247-0.02740.489125
20-0.013213-0.11130.455834
21-0.047206-0.39780.345999
220.0135130.11390.454834
23-0.036235-0.30530.380507
24-0.029305-0.24690.402838
250.0103460.08720.465389
26-0.071556-0.60290.274235
27-0.059549-0.50180.308692
28-0.089154-0.75120.227499
29-0.048846-0.41160.340942
300.0236420.19920.421333
31-0.095101-0.80130.212805
32-0.115956-0.97710.165927
33-0.152542-1.28530.101425
34-0.003266-0.02750.48906
35-0.114694-0.96640.168555
36-0.03274-0.27590.391724
370.1986431.67380.049285
38-0.153999-1.29760.099309
39-0.014295-0.12050.452232
40-0.005351-0.04510.482082
410.0172810.14560.442321
420.0303010.25530.399608
43-0.036975-0.31160.378147
44-0.022951-0.19340.423604
450.0464380.39130.348376
460.0536130.45180.326413
470.0074220.06250.475156
48-0.058268-0.4910.312479
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Nov/18/t1290103005mvtr2ueqngzpu0i/16nru1290103006.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/18/t1290103005mvtr2ueqngzpu0i/16nru1290103006.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/18/t1290103005mvtr2ueqngzpu0i/26nru1290103006.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/18/t1290103005mvtr2ueqngzpu0i/26nru1290103006.ps (open in new window)


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