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Niet-werkende werkzoekenden Nathalie Wouters

R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 19 May 2008 10:36:54 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5.htm/, Retrieved Mon, 19 May 2008 18:38:13 +0200
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
7840 8292 8534 8441 8602 8468 8832 9006 8749 8714 8193 8251 8192 9056 9407 9068 9431 9907 10044 10838 10871 11127 11303 11349 11493 12694 13227 12253 12234 12491 13248 14042 14392 14834 15542 15518 16197 17325 24016 23671 24998 25329 25904 26548 26752 26967 27034 27056 27476 28497 29085 28720 29067 29249 29672 29761 30066 30315 30571 30757 30742 31310 31381 31470 31226 31081 31061 31114 30828 30418 30195 29877 29192 29876 29409 28458 28340 28164 28438 28053
 
Text written by user:
 
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


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
17840NANA0.939270415680332NA
28292NANA0.9889627277396NA
38534NANA1.07130267860911NA
48441NANA1.00825409612190NA
58602NANA1.00876094138095NA
68468NANA1.00444018095532NA
788328554.9631122728508.166666666671.005500179702481.03238317735474
890068730.109752409778554.666666666671.020508465446901.03160215110859
987498665.106154495558622.8751.004897572386881.00968180239326
1087148641.436441805258685.3750.994941086804571.00839716390711
1181938632.969690569088746.041666666670.9870716399021360.949036113140799
1282518540.75903374348840.541666666670.9660900152698110.966073386147695
1381928407.4094907546589510.9392704156803320.974378613175493
1490568977.63881529889077.833333333330.98896272773961.00872848488487
1594079901.604282267899242.583333333331.071302678609110.950048066134733
1690689509.390518161069431.541666666671.008254096121900.95358372155207
1794319746.31196197569661.666666666671.008760941380950.967648074142735
1899079964.381408470449920.333333333331.004440180955320.994241347644354
191004410242.988434788410186.95833333331.005500179702480.98057320516808
201083810690.931726393910476.08333333331.020508465446901.01375635701078
211087110839.662630408610786.83333333331.004897572386881.00289099122915
221112711022.662109557511078.70833333330.994941086804571.00946576148352
231130311181.753176736411328.20833333330.9870716399021361.01084327487356
241134911160.915916407011552.66666666670.9660900152698111.01685202943931
251149311077.598737464611793.83333333330.9392704156803321.03749921552318
261269411927.714632146012060.83333333330.98896272773961.06424410639309
271322713220.990994326612341.04166666671.071302678609111.00045450493658
281225312746.558336109812642.20833333331.008254096121900.961279090159453
291223413086.949914476312973.29166666671.008760941380950.934824392234221
301249113382.784305980813323.6251.004440180955320.933363320696852
311324813768.649127392713693.33333333331.005500179702480.962185896192472
321404214371.097858725714082.29166666671.020508465446900.977100019639357
331439214796.907399736014724.79166666671.004897572386880.97263567387445
341483415570.910920248815650.08333333330.994941086804570.952673872195205
351554216442.310353609816657.66666666670.9870716399021360.945244291450067
361551817123.381968148517724.41666666670.9660900152698110.906246209356616
371619717645.760209247818786.66666666670.9392704156803320.917897546375556
381732519616.158118275619835.08333333330.98896272773960.883200466449084
392401622359.336755697120871.16666666671.071302678609111.07409268273044
402367122072.404598189321891.70833333331.008254096121901.07242506790320
412499823076.499358442422876.08333333331.008760941380951.08326655666925
422532923941.501339857423835.66666666671.004440180955321.05795370308848
432590424922.704516673124786.3751.005500179702481.03937355525242
442654826249.34866348125721.83333333331.020508465446901.01137747607942
452675226527.830435387326398.54166666671.004897572386881.00845035424810
462696726684.444315734526820.1250.994941086804571.01058877902505
472703426848.389733323127200.04166666670.9870716399021361.00691327370172
482705626599.275882922427532.91666666670.9660900152698111.01717054701368
492747626161.733705548227853.250.9392704156803321.05023620793805
502849727833.490629844328144.1250.98896272773961.02383852528523
512908530442.226190579628416.08333333331.071302678609110.955416329210523
522872028930.506949423228693.66666666671.008254096121900.992723703397553
532906729234.438493396528980.54166666671.008760941380950.994272559966071
542924929412.142933756329282.1251.004440180955320.994453211582584
552967229735.0702725729572.41666666671.005500179702480.997878926399304
562976130437.387842116929825.70833333331.020508465446900.977777730282723
573006630185.699469607830038.58333333331.004897572386880.996034563660574
583031530095.80711123730248.83333333330.994941086804571.00728317030850
593057130059.662801804730453.3750.9870716399021361.01701074298693
603075729581.354237556530619.66666666670.9660900152698111.03974279720267
613074228886.204955031030753.8750.9392704156803321.06424502795913
623131030527.425100206930868.1250.98896272773961.02563514273556
633138133163.513544693230956.251.071302678609110.9462507631379
643147031248.105021121330992.29166666671.008254096121901.00710106992820
653122631252.338661511430980.91666666671.008760941380950.999157225902461
663108131065.911840025130928.58333333331.004440180955321.00048568218608
673106130996.88920641530827.33333333331.005500179702481.00206829766555
683111431332.6714146162307031.020508465446900.993020977633135
693082830710.758451179930561.08333333331.004897572386881.00381760512383
703041830199.861366565330353.41666666670.994941086804571.00722316671547
713019529718.423910293530107.66666666670.9870716399021361.01603638507698
722987728853.123634796329865.8750.9660900152698111.03548580660324
7329192NA29635.0416666667NANA
7429876NA29398.2083333333NANA
7529409NANANANA
7628458NANANANA
7728340NANANANA
7828164NANANANA
7928438NANANANA
8028053NANANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/1cqnj1211215011.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/1cqnj1211215011.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/2fbx11211215011.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/2fbx11211215011.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/31y6y1211215011.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/31y6y1211215011.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/4esta1211215011.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211215088z7omrzt0ty663u5/4esta1211215011.ps (open in new window)


 
Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
 
Parameters (R input):
par1 = multiplicative ; 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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Creative Commons License

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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