Home » date » 2010 » Dec » 04 »

ws 9 - faillissementen ACF (2)

*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: Sat, 04 Dec 2010 13:37:24 +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/Dec/04/t12914697528ic5w4ak4qrfgjf.htm/, Retrieved Sat, 04 Dec 2010 14:35:54 +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/Dec/04/t12914697528ic5w4ak4qrfgjf.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
46 62 66 59 58 61 41 27 58 70 49 59 44 36 72 45 56 54 53 35 61 52 47 51 52 63 74 45 51 64 36 30 55 64 39 40 63 45 59 55 40 64 27 28 45 57 45 69 60 56 58 50 51 53 37 22 55 70 62 58 39 49 58 47 42 62 39 40 72 70 54 65
 
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
1-0.511233-3.92690.000114
20.0887710.68190.248998
3-0.115485-0.88710.189325
40.0553880.42540.336031
5-0.042298-0.32490.373203
6-0.018663-0.14340.443251
70.0470630.36150.359508
80.0195150.14990.440678
9-0.060163-0.46210.322847
10-0.005453-0.04190.483366
110.3242652.49070.007791
12-0.417072-3.20360.001095
130.0908840.69810.24393
140.022930.17610.4304
150.0438430.33680.368746
16-0.015105-0.1160.454014
17-0.054574-0.41920.3383
180.0687670.52820.299667
19-0.002083-0.0160.493645
20-0.096202-0.73890.231437
210.0390320.29980.382686
220.1333711.02440.154905
23-0.086999-0.66830.253288
24-0.079588-0.61130.271666
250.2075281.59410.058134
26-0.239412-1.8390.035478
270.1449881.11370.134968
28-0.144962-1.11350.13501
290.2090921.60610.0568
30-0.108513-0.83350.203962
31-0.064239-0.49340.31177
320.1029690.79090.21608
330.0522260.40120.344878
34-0.085521-0.65690.256899
35-0.025547-0.19620.422551
360.0419650.32230.374168
37-0.130913-1.00560.159367
380.1658081.27360.1039
39-0.101437-0.77910.219503
400.1507421.15790.12579
41-0.177953-1.36690.088424
420.0729720.56050.288628
430.042910.32960.371436
44-0.010028-0.0770.469433
45-0.076522-0.58780.279463
46-0.004938-0.03790.484935
470.0565080.4340.332918
48-0.017645-0.13550.446326


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.511233-3.92690.000114
2-0.233657-1.79480.038908
3-0.256263-1.96840.026864
4-0.184354-1.4160.081009
5-0.183561-1.410.0819
6-0.231754-1.78010.040101
7-0.172939-1.32840.094586
8-0.107066-0.82240.207084
9-0.182652-1.4030.082932
10-0.245783-1.88790.03198
110.3380652.59670.005931
12-0.021801-0.16750.43379
13-0.192832-1.48120.071941
14-0.023784-0.18270.427833
15-0.020807-0.15980.436783
16-0.018186-0.13970.44469
17-0.107145-0.8230.206912
18-0.133437-1.0250.154785
19-0.068288-0.52450.300939
20-0.160527-1.2330.111227
21-0.341173-2.62060.005572
22-0.228632-1.75620.042126
230.1823121.40040.08332
24-0.153807-1.18140.121089
250.0661940.50840.306517
26-0.102879-0.79020.216279
270.001170.0090.49643
28-0.032504-0.24970.401856
290.0293840.22570.411106
300.024050.18470.427035
31-0.049991-0.3840.351185
32-0.043589-0.33480.369475
33-0.123506-0.94870.17333
340.0453260.34820.364482
350.1960451.50580.068721
36-0.036125-0.27750.391191
37-0.054987-0.42240.337149
380.0012720.00980.496119
390.0266530.20470.419245
400.0095520.07340.47088
41-0.055058-0.42290.336951
420.0836570.64260.261493
430.1026890.78880.216703
44-0.000785-0.0060.497606
45-0.118126-0.90730.183959
46-0.006589-0.05060.479903
470.1160810.89160.188106
48-0.028806-0.22130.412826
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/04/t12914697528ic5w4ak4qrfgjf/1o29t1291469842.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/04/t12914697528ic5w4ak4qrfgjf/1o29t1291469842.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/04/t12914697528ic5w4ak4qrfgjf/2o29t1291469842.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/04/t12914697528ic5w4ak4qrfgjf/2o29t1291469842.ps (open in new window)


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