Home » date » 2009 » Jun » 07 »

Annelies Reul bankbiljetten in circulatie oef 9

*Unverified author*
R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Sun, 07 Jun 2009 14:40:42 -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/Jun/07/t12444073548q2qcn8p52s6pgm.htm/, Retrieved Sun, 07 Jun 2009 22:42:39 +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/Jun/07/t12444073548q2qcn8p52s6pgm.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 «
334053 326018 326894 330958 333913 337042 342103 344795 342060 342535 343083 354261 363049 347562 347577 349715 353818 354073 357040 359177 354845 354481 352747 360446 368285 354819 353017 354551 352682 351146 350760 347555 335363 325165 311274 297987 344276 306152 283323 285869 293660 300831 313351 322765 323613 329199 334038 350683 353929 340715 347752 358474 366179 373163 382739 391636 391693 395453 399368 416075 427623 418000 425316 436397 442533 449148 460852 462789 465097 469728 475434 495992 487101 489496 498649 505533 512839 522584 532603 531520 531623 535608 539804 559182 548414 550774 556397 569125 571988 578807 588234 588724 588550 592764 598593 619494 604560 606210 614823 620033 625236 631307 639704 639223 637312 640124 644649 668209 651667 653170 662102 667617 671420 677156 686086 684954 684331 722145 731098 753123 740228 741472 747315 757533
 
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'George Udny Yule' @ 72.249.76.132


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1334053NANA1.02239875865071NA
2326018NANA0.988163293286403NA
3326894NANA0.983463519347805NA
4330958NANA0.99098119169452NA
5333913NANA0.995158088533445NA
6337042NANA0.999396965563874NA
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8344795344540.731000323341456.9166666671.009031342412861.00073799402160
9342060342206.4925539343216.3750.9970575924703480.999571917666416
10342535344353.646521115344859.7083333330.9985325574429560.994718666291214
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13363049357166.443745023349341.6251.022398758650711.01647006978958
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16349715349544.501494577352725.6666666670.990981191694521.00048777338706
17353818351913.857145569353626.0833333330.9951580885334451.00541082090338
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22354481355717.321474525356240.0833333330.9985325574429560.996524427122637
23352747354075.995354982356394.250.993495252392490.996246581602773
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73487101501143.192935114490164.1251.022398758650710.971979679394884
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77512839510115.2994975512597.250.9951580885334451.00533938210672
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83539804539803.019718627543337.2916666670.993495252392491.00000181599831
84559182554746.231015754548144.4583333331.012043855560441.00799603266547
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88569125561901.613317498567015.4166666670.990981191694521.01285525172255
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107644649644398.572451227648617.6666666670.993495252392491.00038862213462
108668209660310.417164564652452.3751.012043855560441.0119619237106
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110653170652319.569848268660133.3750.9881632932864031.00130370173001
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113671420673119.167460093676394.2083333330.9951580885334450.99747568106476
114677156683122.138592059683534.3333333330.9993969655638740.99126636621036
115686086697861.826586328690762.4583333331.010277582644150.98312584792905
116684954704436.81688354698131.751.009031342412860.972342704957227
117684331703286.08055534705361.5416666670.9970575924703480.973047837744248
118722145711612.797799508712658.5833333330.9985325574429561.01480046766031
119731098NANA0.99349525239249NA
120753123NANA1.01204385556044NA
121740228NANANANA
122741472NANANANA
123747315NANANANA
124757533NANANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/1vzvc1244407240.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/1vzvc1244407240.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/2zamy1244407240.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/2zamy1244407240.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/30sg31244407240.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/30sg31244407240.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/4eknz1244407240.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t12444073548q2qcn8p52s6pgm/4eknz1244407240.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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Software written by Ed van Stee & Patrick Wessa


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