Home » date » 2009 » Aug » 19 »

Klassieke decompositie - Gem. prijs gebakken tong of forel - Niels Braspennincx

*Unverified author*
R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Tue, 18 Aug 2009 16:30:39 -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/Aug/19/t1250634701f2ga5wk7wsr1a6a.htm/, Retrieved Wed, 19 Aug 2009 00:31:41 +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/Aug/19/t1250634701f2ga5wk7wsr1a6a.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 «
15,22 15,27 15,31 15,33 15,42 15,49 15,65 15,67 15,69 15,83 15,92 15,99 15,94 15,96 16,03 16,09 16,04 16,23 16,2 16,2 16,26 16,28 16,27 16,29 16,3 16,37 16,39 16,42 16,43 16,37 16,37 16,39 16,48 16,51 16,5 16,54 16,52 16,56 16,61 16,75 16,75 16,79 16,82 16,84 17,14 17,25 17,28 17,3 17,34 17,44 17,48 17,55 17,59 17,66 17,67 17,64 17,68 17,72 17,78 17,83 17,88 18,11 18,16 18,27 18,29 18,35 18,35 18,38 18,41 18,41 18,42 18,43 18,48 18,54 18,65 18,66 18,69 18,72 18,72 18,73 18,84 18,83 18,91 18,91 18,94 18,97 19 19,08 19,18 19,24 19,23 19,25 19,3 19,33 19,35 19,35 19,31 19,47 19,7 19,76 19,9 19,97 20,1 20,26 20,44 20,43 20,57 20,6 20,69 20,93 20,98 21,11 21,14 21,16 21,32 21,32 21,48 21,58 21,74 21,75 21,81 21,89 22,21 22,37 22,47 22,51 22,55 22,61 22,58 22,85 22,93 22,98
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
115.22NANA-0.0659131944444443NA
215.27NANA-0.0205798611111119NA
315.31NANA0.0187951388888892NA
415.33NANA0.0458368055555562NA
515.42NANA0.0293784722222218NA
615.49NANA0.0230451388888882NA
715.6515.596711805555615.59583333333330.0008784722222218090.0532881944444448
815.6715.625420138888915.6545833333333-0.02916319444444290.0445798611111083
915.6915.731836805555615.71333333333330.0185034722222223-0.0418368055555582
1015.8315.780420138888915.7750.005420138888888790.0495798611111127
1115.9215.836211805555615.83250.003711805555555940.0837881944444447
1215.9915.859253472222215.8891666666667-0.02991319444444510.130746527777781
1315.9415.877003472222215.9429166666667-0.06591319444444430.0629965277777771
1415.9615.967336805555615.9879166666667-0.0205798611111119-0.00733680555554983
1516.0316.052545138888916.033750.0187951388888892-0.0225451388888871
1616.0916.122086805555616.076250.0458368055555562-0.0320868055555543
1716.0416.138961805555616.10958333333330.0293784722222218-0.0989618055555539
1816.2316.159711805555616.13666666666670.02304513888888820.0702881944444478
1916.216.165045138888916.16416666666670.0008784722222218090.0349548611111103
2016.216.167086805555616.19625-0.02916319444444290.0329131944444470
2116.2616.246836805555616.22833333333330.01850347222222230.0131631944444486
2216.2816.262503472222216.25708333333330.005420138888888790.0174965277777801
2316.2716.290795138888916.28708333333330.00371180555555594-0.0207951388888930
2416.2916.279253472222216.3091666666667-0.02991319444444510.0107465277777798
2516.316.256170138888916.3220833333333-0.06591319444444430.0438298611111101
2616.3716.316503472222216.3370833333333-0.02057986111111190.0534965277777779
2716.3916.372961805555616.35416666666670.01879513888888920.0170381944444422
2816.4216.418753472222216.37291666666670.04583680555555620.00124652777778067
2916.4316.421461805555616.39208333333330.02937847222222180.0085381944444407
3016.3716.435128472222216.41208333333330.0230451388888882-0.0651284722222236
3116.3716.432545138888916.43166666666670.000878472222221809-0.0625451388888898
3216.3916.419586805555616.44875-0.0291631944444429-0.0295868055555530
3316.4816.484336805555616.46583333333330.0185034722222223-0.00433680555555327
3416.5116.494170138888916.488750.005420138888888790.0158298611111150
3516.516.519545138888916.51583333333330.00371180555555594-0.019545138888887
3616.5416.516753472222216.5466666666667-0.02991319444444510.0232465277777791
3716.5216.517003472222216.5829166666667-0.06591319444444430.00299652777777837
3816.5616.599836805555616.6204166666667-0.0205798611111119-0.0398368055555558
3916.6116.685461805555616.66666666666670.0187951388888892-0.075461805555559
4016.7516.770836805555616.7250.0458368055555562-0.0208368055555574
4116.7516.817711805555616.78833333333330.0293784722222218-0.0677118055555574
4216.7916.875545138888916.85250.0230451388888882-0.0855451388888895
4316.8216.919211805555616.91833333333330.000878472222221809-0.099211805555555
4416.8416.960003472222216.9891666666667-0.0291631944444429-0.120003472222223
4517.1417.080586805555617.06208333333330.01850347222222230.0594131944444456
4617.2517.137086805555617.13166666666670.005420138888888790.112913194444449
4717.2817.203711805555617.20.003711805555555940.0762881944444445
4817.317.241336805555617.27125-0.02991319444444510.0586631944444491
4917.3417.277003472222217.3429166666667-0.06591319444444430.0629965277777806
5017.4417.391086805555617.4116666666667-0.02057986111111190.0489131944444452
5117.4817.486295138888917.46750.0187951388888892-0.00629513888888766
5217.5517.555420138888917.50958333333330.0458368055555562-0.00542013888889059
5317.5917.579378472222217.550.02937847222222180.0106215277777757
5417.6617.615961805555617.59291666666670.02304513888888820.0440381944444432
5517.6717.638378472222217.63750.0008784722222218090.0316215277777765
5617.6417.658753472222217.6879166666667-0.0291631944444429-0.0187534722222189
5717.6817.762670138888917.74416666666670.0185034722222223-0.0826701388888829
5817.7217.807920138888917.80250.00542013888888879-0.0879201388888866
5917.7817.865378472222217.86166666666670.00371180555555594-0.0853784722222244
6017.8317.889670138888917.9195833333333-0.0299131944444451-0.0596701388888867
6117.8817.910753472222217.9766666666667-0.0659131944444443-0.0307534722222229
6218.1118.015253472222218.0358333333333-0.02057986111111190.0947465277777795
6318.1618.115878472222218.09708333333330.01879513888888920.0441215277777758
6418.2718.202086805555618.156250.04583680555555620.0679131944444435
6518.2918.241045138888918.21166666666670.02937847222222180.0489548611111061
6618.3518.286378472222218.26333333333330.02304513888888820.0636215277777801
6718.3518.314211805555618.31333333333330.0008784722222218090.0357881944444465
6818.3818.327086805555618.35625-0.02916319444444290.0529131944444465
6918.4118.413086805555618.39458333333330.0185034722222223-0.00308680555555441
7018.4118.436670138888918.431250.00542013888888879-0.0266701388888855
7118.4218.467878472222218.46416666666670.00371180555555594-0.047878472222223
7218.4318.466336805555618.49625-0.0299131944444451-0.0363368055555569
7318.4818.461170138888918.5270833333333-0.06591319444444430.0188298611111115
7418.5418.536503472222218.5570833333333-0.02057986111111190.0034965277777772
7518.6518.608378472222218.58958333333330.01879513888888920.0416215277777745
7618.6618.670836805555618.6250.0458368055555562-0.0108368055555523
7718.6918.692295138888918.66291666666670.0293784722222218-0.00229513888888988
7818.7218.726378472222218.70333333333330.0230451388888882-0.00637847222222732
7918.7218.743378472222218.74250.000878472222221809-0.0233784722222268
8018.7318.750420138888918.7795833333333-0.0291631944444429-0.0204201388888912
8118.8418.830586805555618.81208333333330.01850347222222230.00941319444444488
8218.8318.849586805555618.84416666666670.00542013888888879-0.0195868055555550
8318.9118.885795138888918.88208333333330.003711805555555940.0242048611111123
8418.9118.894253472222218.9241666666667-0.02991319444444510.0157465277777824
8518.9418.901170138888918.9670833333333-0.06591319444444430.0388298611111111
8618.9718.989420138888919.01-0.0205798611111119-0.0194201388888899
871919.069628472222219.05083333333330.0187951388888892-0.0696284722222238
8819.0819.136670138888919.09083333333330.0458368055555562-0.0566701388888866
8919.1819.159378472222219.130.02937847222222180.0206215277777773
9019.2419.189711805555619.16666666666670.02304513888888820.0502881944444411
9119.2319.201295138888919.20041666666670.0008784722222218090.0287048611111125
9219.2519.207503472222219.2366666666667-0.02916319444444290.0424965277777822
9319.319.305170138888919.28666666666670.0185034722222223-0.0051701388888894
9419.3319.349586805555619.34416666666670.00542013888888879-0.0195868055555550
9519.3519.406211805555619.40250.00371180555555594-0.0562118055555558
9619.3519.433003472222219.4629166666667-0.0299131944444451-0.0830034722222202
9719.3119.463670138888919.5295833333333-0.0659131944444443-0.153670138888891
9819.4719.587336805555619.6079166666667-0.0205798611111119-0.117336805555556
9919.719.716295138888919.69750.0187951388888892-0.0162951388888892
10019.7619.836670138888919.79083333333330.0458368055555562-0.0766701388888862
10119.919.916878472222219.88750.0293784722222218-0.0168784722222206
10219.9720.013461805555619.99041666666670.0230451388888882-0.0434618055555553
10320.120.100878472222220.10.000878472222221809-0.000878472222218818
10420.2620.189170138888920.2183333333333-0.02916319444444290.0708298611111111
10520.4420.351003472222220.33250.01850347222222230.0889965277777769
10620.4320.447503472222220.44208333333330.00542013888888879-0.0175034722222200
10720.5720.553711805555620.550.003711805555555940.0162881944444422
10820.620.621336805555620.65125-0.0299131944444451-0.0213368055555527
10920.6920.685753472222220.7516666666667-0.06591319444444430.00424652777778078
11020.9320.826086805555620.8466666666667-0.02057986111111190.103913194444445
11120.9820.952961805555620.93416666666670.01879513888888920.0270381944444438
11221.1121.071253472222221.02541666666670.04583680555555620.038746527777775
11321.1421.151461805555621.12208333333330.0293784722222218-0.0114618055555553
11421.1621.241795138888921.218750.0230451388888882-0.0817951388888929
11521.3221.314211805555621.31333333333330.0008784722222218090.00578819444444179
11621.3221.370836805555621.4-0.0291631944444429-0.0508368055555586
11721.4821.509753472222221.491250.0185034722222223-0.0297534722222217
11821.5821.600420138888921.5950.00542013888888879-0.0204201388888912
11921.7421.706628472222221.70291666666670.003711805555555940.0333715277777742
12021.7521.784670138888921.8145833333333-0.0299131944444451-0.0346701388888917
12121.8121.856170138888921.9220833333333-0.0659131944444443-0.0461701388888862
12221.8922.006503472222222.0270833333333-0.0205798611111119-0.116503472222217
12322.2122.145461805555622.12666666666670.01879513888888920.0645381944444452
12422.3722.271253472222222.22541666666670.04583680555555620.0987465277777773
12522.4722.357295138888922.32791666666670.02937847222222180.112704861111109
12622.5122.451795138888922.428750.02304513888888820.0582048611111112
12722.55NANA0.000878472222221809NA
12822.61NANA-0.0291631944444429NA
12922.58NANA0.0185034722222223NA
13022.85NANA0.00542013888888879NA
13122.93NANA0.00371180555555594NA
13222.98NANA-0.0299131944444451NA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/1tkic1250634634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/1tkic1250634634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/28z3g1250634634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/28z3g1250634634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/3hp8r1250634634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/3hp8r1250634634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/4n07u1250634634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/19/t1250634701f2ga5wk7wsr1a6a/4n07u1250634634.ps (open in new window)


 
Parameters (Session):
par1 = additive ; par2 = 12 ;
 
Parameters (R input):
par1 = additive ; par2 = 12 ;
 
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
 





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