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Opgave 6bis: gedifferentieerd - Aantal nieuwe gebouwen - Christophe Morre

*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, 14 May 2009 03:55:24 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/May/14/t1242294964pcmcd533yncq0a6.htm/, Retrieved Thu, 14 May 2009 11:56:06 +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/2009/May/14/t1242294964pcmcd533yncq0a6.htm/},
    year = {2009},
}
@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 = {2009},
    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 «
2194 2419 2742 2137 2710 2173 2363 2126 1905 2121 1983 1734 2074 2049 2406 2558 2251 2059 2397 1747 1707 2319 1631 1627 1791 2034 1997 2169 2028 2253 2218 1855 2187 1852 1570 1851 1954 1828 2251 2277 2085 2282 2266 1878 2267 2069 1746 2299 2360 2214 2825 2355 2333 3016 2155 2172 2150 2533 2058 2160 2260 2498 2695 2799 2945 2930 2318 2540 2570 2669 2450 2842 3440 2678 2981 2259 2844 2546 2456 2295 2379 2479 2057 2280 2351 2275 2543 2305 2188 2720 2398 2147 1898 2538 2081 2057 2497 2460 2195 2823 2100 2640 2342 2171 2482
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.513415-5.23580
2-0.004803-0.0490.480515
30.1960581.99940.024086
4-0.112899-1.15130.126115
5-0.078063-0.79610.213898
60.0604560.61650.269446
7-0.131711-1.34320.091066
80.0108360.11050.45611
90.1436091.46450.073033
10-0.133585-1.36230.088023
11-0.02247-0.22910.409601
120.2597032.64850.004673
13-0.153537-1.56580.060219
14-0.028441-0.290.386179
150.1955661.99440.024363
16-0.230116-2.34670.010417
170.1249521.27430.102704
18-0.091054-0.92860.17763
19-0.003636-0.03710.485245
20-0.093323-0.95170.171725
210.1924821.96290.026162
22-0.19963-2.03580.022155
230.1139371.16190.123962
240.0626850.63930.262027
25-0.004226-0.04310.482855
26-0.02707-0.27610.391526
270.0470620.47990.31614
28-0.061258-0.62470.266766
290.0076050.07760.469165
300.008550.08720.465341
31-0.203015-2.07040.020448
320.1922311.96040.026313
33-0.047835-0.48780.313351
34-0.004673-0.04770.481041
35-0.031737-0.32370.373424
360.1608811.64070.051944
37-0.062353-0.63590.263125
38-0.024739-0.25230.400659
39-0.004749-0.04840.480734
400.0437930.44660.328044
41-0.092233-0.94060.174547
42-0.002067-0.02110.49161
430.0097140.09910.46064
440.0424150.43260.333118
45-0.121466-1.23870.10912
460.1328661.3550.089182
47-0.05395-0.55020.291687
480.022550.230.409287


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.513415-5.23580
2-0.36447-3.71690.000163
30.0087210.08890.46465
40.0416280.42450.336032
5-0.106595-1.08710.139762
6-0.138201-1.40940.080853
7-0.278121-2.83630.002743
8-0.280233-2.85780.002577
9-0.013304-0.13570.446169
10-0.006221-0.06340.474768
11-0.174928-1.78390.038677
120.0661110.67420.250838
130.0890990.90860.182822
14-0.004316-0.0440.48249
150.1568131.59920.056407
16-0.013055-0.13310.447171
170.0982391.00180.159372
18-0.055791-0.5690.285304
190.0396420.40430.343423
20-0.166433-1.69730.046316
210.0192380.19620.422422
22-0.095635-0.97530.165841
23-0.025535-0.26040.39753
24-0.068111-0.69460.244429
250.0959860.97890.164958
260.0405020.4130.340214
27-0.021645-0.22070.412863
28-0.017121-0.17460.430865
29-0.025991-0.26510.395746
300.0419760.42810.334742
31-0.220356-2.24720.01337
32-0.047219-0.48150.315571
33-0.064474-0.65750.256153
340.0743820.75860.224917
35-0.083489-0.85140.198245
36-0.011229-0.11450.454528
370.054990.56080.288073
38-0.076629-0.78150.218153
39-0.070336-0.71730.237402
40-0.034332-0.35010.36348
41-0.017934-0.18290.42762
42-0.174301-1.77750.039203
430.0839640.85630.196908
440.0860090.87710.19122
45-0.137297-1.40020.08222
46-0.046673-0.4760.317546
47-0.070627-0.72030.23649
48-0.037854-0.3860.35013
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/14/t1242294964pcmcd533yncq0a6/1vcrj1242294922.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/14/t1242294964pcmcd533yncq0a6/1vcrj1242294922.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/14/t1242294964pcmcd533yncq0a6/2ni7o1242294922.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/14/t1242294964pcmcd533yncq0a6/2ni7o1242294922.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
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 (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='lags',ylab='ACF')
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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