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Autocorrelatie functie (d) 1

*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: Wed, 22 Dec 2010 14:25:17 +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/22/t1293027811eyiew2j9zlm5t07.htm/, Retrieved Wed, 22 Dec 2010 15:23:32 +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/22/t1293027811eyiew2j9zlm5t07.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 «
716 677 710 839 886 891 917 820 793 932 906 844 801 957 1159 1264 1097 1240 1411 1535 1862 1894 2239 2465 2423 2692 2856 3450 4162 4260 4225 4092 4160 3896 3628 3754 3749 3907 4449 5272 6197 6446 7157 7559 7674 6929 7156 6805 7095 7222 7593 7910 7878
 
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'RServer@AstonUniversity' @ vre.aston.ac.uk


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3674572.64980.005322
20.2992172.15770.017797
30.0110780.07990.468317
4-0.043743-0.31540.376847
5-0.283871-2.0470.022862
6-0.376336-2.71380.004501
7-0.268385-1.93530.029197
8-0.134138-0.96730.16894
9-0.135471-0.97690.166572
100.024320.17540.430733
110.1818331.31120.097773
120.1704161.22890.112323
130.1248970.90060.185964
140.157551.13610.13056
150.1108060.7990.213953
16-0.007841-0.05650.477565
17-0.115031-0.82950.205306
18-0.060197-0.43410.333009
19-0.054157-0.39050.348869
20-0.032815-0.23660.406936
210.031370.22620.410963
220.0104790.07560.470027
230.0268210.19340.423697
24-0.018982-0.13690.445827
25-0.044434-0.32040.374969
264.9e-054e-040.499861
27-0.087982-0.63440.264285
28-0.004565-0.03290.486934
290.0385450.2780.391076
30-0.049508-0.3570.361266
31-0.040061-0.28890.386909
32-0.09737-0.70210.242861
33-0.037257-0.26870.394626
34-0.052998-0.38220.351946
35-0.042391-0.30570.380532
36-0.033562-0.2420.404858
37-0.009705-0.070.472237
38-0.039181-0.28250.389326
39-0.02278-0.16430.435078
400.0169720.12240.451533
41-0.008094-0.05840.476839
42-0.001096-0.00790.496862
430.0084270.06080.475889
440.0226960.16370.435315
450.0055160.03980.484212
460.0102750.07410.470609
47-0.004975-0.03590.485758
48-0.002008-0.01450.494252


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3674572.64980.005322
20.1898231.36880.088468
3-0.177202-1.27780.103494
4-0.067956-0.490.313085
5-0.250677-1.80770.038223
6-0.254061-1.83210.036336
70.0347830.25080.401469
80.0807770.58250.281377
9-0.132826-0.95780.171292
100.0396390.28580.388068
110.1332790.96110.170477
12-0.091966-0.66320.255073
13-0.038387-0.27680.39151
140.1336430.96370.169826
15-0.024568-0.17720.430033
16-0.070652-0.50950.306286
170.0076690.05530.478056
180.043160.31120.378434
190.0134750.09720.461483
200.1032840.74480.229874
210.0946960.68290.248862
22-0.160091-1.15440.1268
23-0.025114-0.18110.428495
240.0427070.3080.379669
25-0.124254-0.8960.187188
260.069710.50270.308654
270.0064380.04640.481575
28-0.015796-0.11390.454875
290.0739510.53330.298061
30-0.14605-1.05320.148563
31-0.10738-0.77430.221122
32-0.078908-0.5690.285897
33-0.002776-0.020.492053
34-0.006682-0.04820.480878
35-0.018609-0.13420.446884
36-0.061473-0.44330.329699
37-0.06313-0.45520.325417
38-0.039043-0.28150.389707
39-0.062717-0.45230.326481
400.0008250.00590.497639
41-0.040099-0.28920.386806
42-0.041617-0.30010.382646
430.0186290.13430.446828
44-0.015536-0.1120.455615
450.0139260.10040.460197
460.0780360.56270.28802
47-0.053503-0.38580.350603
48-0.031118-0.22440.411666
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/1m7g81293027913.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/1m7g81293027913.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/2xyfb1293027913.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/2xyfb1293027913.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/3q7ew1293027913.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/22/t1293027811eyiew2j9zlm5t07/3q7ew1293027913.ps (open in new window)


 
Parameters (Session):
 
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 1 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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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