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Inschrijving nieuwe personenwagens

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R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Sun, 21 Nov 2010 10:14:46 +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/21/t1290334514di91yfq2x3wj5cu.htm/, Retrieved Sun, 21 Nov 2010 11:15:14 +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/21/t1290334514di91yfq2x3wj5cu.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:
KDGP2W11
 
Dataseries X:
» Textbox « » Textfile « » CSV «
41086 39690 43129 37863 35953 29133 24693 22205 21725 27192 21790 13253 37702 30364 32609 30212 29965 28352 25814 22414 20506 28806 22228 13971 36845 35338 35022 34777 26887 23970 22780 17351 21382 24561 17409 11514 31514 27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698
 
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
1-0.29901-2.51950.007002
2-0.125252-1.05540.147412
30.141091.18880.11923
4-0.134876-1.13650.129788
50.0392150.33040.371025
6-0.092414-0.77870.219375
7-0.070657-0.59540.276744
8-0.027595-0.23250.408401
90.0816890.68830.246746
10-0.124057-1.04530.14971
11-0.220857-1.8610.033444
120.6942595.84990
13-0.198323-1.67110.049552
14-0.098196-0.82740.205388
150.1315151.10820.135766
16-0.173331-1.46050.07428
170.0649480.54730.292959
18-0.061006-0.5140.304408
19-0.10727-0.90390.18456
200.0778460.65590.256989
210.0005460.00460.49817
22-0.132975-1.12050.133146
23-0.10805-0.91040.182834
240.5041354.24793.2e-05
25-0.158231-1.33330.093352
26-0.00396-0.03340.486739
270.017580.14810.441328
28-0.106521-0.89760.186225
290.1074130.90510.184242
30-0.115098-0.96980.167711
31-0.068804-0.57980.281959
320.0574630.48420.314869
330.0131230.11060.456133
34-0.075043-0.63230.264603
35-0.080564-0.67880.249721
360.3015132.54060.006627
37-0.097891-0.82480.206112
380.0225690.19020.424859
390.0114430.09640.461731
40-0.107815-0.90850.183352
410.1198721.01010.157949
42-0.127614-1.07530.142943
43-0.003439-0.0290.488481
440.0478510.40320.344005
45-0.051805-0.43650.331892
460.0150520.12680.449717
47-0.10213-0.86060.196187
480.2016931.69950.046802


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.29901-2.51950.007002
2-0.235736-1.98630.025428
30.0282830.23830.406162
4-0.120382-1.01440.156929
5-0.013668-0.11520.454318
6-0.152886-1.28820.100922
7-0.154438-1.30130.098678
8-0.196303-1.65410.051263
9-0.02271-0.19140.424396
10-0.196904-1.65910.050749
11-0.448937-3.78280.00016
120.5206094.38672e-05
130.1388321.16980.122993
140.0415340.350.363696
15-0.041634-0.35080.363384
16-0.060008-0.50560.307339
17-0.121125-1.02060.15545
18-0.059157-0.49850.30985
19-0.010749-0.09060.464044
200.08540.71960.237068
21-0.060382-0.50880.306239
22-0.111788-0.94190.174707
23-0.023929-0.20160.420392
240.0780420.65760.256463
25-0.044485-0.37480.354451
260.1262361.06370.145539
27-0.143154-1.20620.115865
280.0314980.26540.395732
290.0380830.32090.374618
30-0.038024-0.32040.374803
310.0221410.18660.426267
32-0.132996-1.12060.133108
330.0345980.29150.385747
340.1111930.93690.175986
350.0568810.47930.316603
36-0.135844-1.14460.128101
37-0.060346-0.50850.306344
38-0.127665-1.07570.142845
390.0816970.68840.246726
40-0.005407-0.04560.481894
410.0119570.10080.460016
42-0.027509-0.23180.408682
430.0283520.23890.405937
44-0.018327-0.15440.438857
45-0.025789-0.21730.414299
46-0.015715-0.13240.447516
47-0.065201-0.54940.29223
48-0.033106-0.2790.390543
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Nov/21/t1290334514di91yfq2x3wj5cu/1og0a1290334482.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/21/t1290334514di91yfq2x3wj5cu/1og0a1290334482.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/21/t1290334514di91yfq2x3wj5cu/2z8hd1290334482.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/21/t1290334514di91yfq2x3wj5cu/2z8hd1290334482.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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This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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