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Classical Decompostion - Openstaande Jobvacatures

*The author of this computation has been verified*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 27 Dec 2010 14:51:09 +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/Dec/27/t12934613908orw2jy0mltk4dn.htm/, Retrieved Mon, 27 Dec 2010 15:49:55 +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/Dec/27/t12934613908orw2jy0mltk4dn.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
20503 22885 26217 26583 27751 28158 27373 28367 26851 26733 26849 26733 27951 29781 32914 33488 35652 36488 35387 35676 34844 32447 31068 29010 29812 30951 32974 32936 34012 32946 31948 30599 27691 25073 23406 22248 22896 25317 26558 26471 27543 26198 24725 25005 23462 20780 19815 19761 21454 23899 24939 23580 24562 24696 23785 23812 21917 19713 19282 18788 21453 24482 27474 27264 27349 30632 29429 30084 26290 24379 23335 21346 21106 24514 28353 30805 31348 34556 33855 34787 32529 29998 29257 28155 30466 35704 39327 39351 42234 43630 43722 43121 37985 37135 34646 33026 35087 38846 42013 43908 42868 44423 44167 43636 44382 42142 43452 36912 42413 45344 44873 47510 49554 47369 45998 48140 48441 44928 40454 38661 37246 36843 36424 37594 38144 38737 34560 36080 33508 35462 33374 32110 35533 35532 37903 36763 40399 44164 44496 43110 43880 43930 44327
 
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'George Udny Yule' @ 72.249.76.132


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
120503NANA-3343.44097222222NA
222885NANA-825.824305555556NA
326217NANA1131.10069444444NA
426583NANA1772.79236111111NA
527751NANA2745.13402777778NA
628158NANA3336.44236111111NA
72737328633.129861111126560.58333333332072.54652777778-1260.12986111111
82836729511.642361111127158.252353.39236111111-1144.64236111111
92685128044.167361111127724.625319.542361111111-1193.16736111111
102673326677.284027777828291.375-1614.0909722222255.7159722222277
112684925863.975694444428908.2916666667-3044.31597222222985.024305555558
122673324681.304861111129584.5833333333-4903.278472222222051.69513888889
132795126922.142361111130265.5833333333-3343.440972222221028.85763888889
142978130078.217361111130904.0416666667-825.824305555556-297.217361111107
153291432672.725694444431541.6251131.10069444444241.274305555558
163348833885.542361111132112.751772.79236111111-397.542361111115
173565235271.759027777832526.6252745.13402777778380.240972222226
183648836133.734027777832797.29166666673336.44236111111354.265972222223
193538735042.254861111132969.70833333332072.54652777778344.745138888895
203567635449.3923611111330962353.39236111111226.607638888891
213484433466.792361111133147.25319.5423611111111377.20763888889
223244731512.659027777833126.75-1614.09097222222934.340972222213
233106829991.100694444433035.4166666667-3044.315972222221076.89930555555
242901027916.221527777832819.5-4903.278472222221093.77847222222
252981229185.184027777832528.625-3343.44097222222626.815972222219
263095131347.967361111132173.7916666667-825.824305555556-396.96736111111
273297432795.309027777831664.20833333331131.10069444444178.690972222226
283293632831.709027777831058.91666666671772.79236111111104.290972222225
293401233177.550694444430432.41666666672745.13402777778834.449305555558
303294633167.859027777829831.41666666673336.44236111111-221.859027777777
313194831334.046527777829261.52072.54652777778613.95347222222
323059931091.975694444428738.58333333332353.39236111111-492.975694444442
332769128556.042361111128236.5319.542361111111-865.042361111111
342507326085.700694444427699.7916666667-1614.09097222222-1012.70069444444
352340624116.559027777827160.875-3044.31597222222-710.559027777777
362224821706.888194444426610.1666666667-4903.27847222222541.111805555556
372289622684.600694444426028.0416666667-3343.44097222222211.399305555555
382531724668.175694444425494-825.824305555556648.824305555561
392655826215.809027777825084.70833333331131.10069444444342.190972222223
402647126502.417361111124729.6251772.79236111111-31.4173611111109
412754327146.259027777824401.1252745.13402777778396.740972222222
422619827484.317361111124147.8753336.44236111111-1286.31736111111
432472526056.713194444423984.16666666672072.54652777778-1331.71319444444
442500526218.3923611111238652353.39236111111-1213.39236111111
452346224058.000694444423738.4583333333319.542361111111-596.000694444443
462078021936.450694444423550.5416666667-1614.09097222222-1156.45069444444
471981520261.559027777823305.875-3044.31597222222-446.559027777777
481976118215.804861111123119.0833333333-4903.278472222221545.19513888889
492145419673.892361111123017.3333333333-3343.440972222221780.10763888889
502389922102.634027777822928.4583333333-825.8243055555561796.36597222222
512493923945.475694444422814.3751131.10069444444993.524305555558
522358024478.334027777822705.54166666671772.79236111111-898.334027777779
532456225384.009027777822638.8752745.13402777778-822.009027777778
542469625912.567361111122576.1253336.44236111111-1216.56736111111
552378524608.088194444422535.54166666672072.54652777778-823.088194444448
562381224913.184027777822559.79166666672353.39236111111-1101.18402777778
572191723009.250694444422689.7083333333319.542361111111-1092.25069444444
581971321334.742361111122948.8333333333-1614.09097222222-1621.74236111111
591928220174.142361111123218.4583333333-3044.31597222222-892.14236111111
601878818678.638194444423581.9166666667-4903.27847222222109.361805555556
612145320720.975694444424064.4166666667-3343.44097222222732.024305555558
622448223735.092361111124560.9166666667-825.824305555556746.90763888889
632747426135.559027777825004.45833333331131.100694444441338.44097222223
642726427153.875694444425381.08333333331772.79236111111110.124305555553
652734928489.509027777825744.3752745.13402777778-1140.50902777778
663063229356.275694444426019.83333333333336.442361111111275.72430555556
672942928184.504861111126111.95833333332072.546527777781244.49513888889
683008428452.225694444426098.83333333332353.392361111111631.77430555556
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702437924706.867361111126320.9583333333-1614.09097222222-327.867361111112
712333523590.809027777826635.125-3044.31597222222-255.809027777785
722134622061.971527777826965.25-4903.27847222222-715.97152777778
732110623969.725694444427313.1666666667-3343.44097222222-2863.72569444444
742451426867.717361111127693.5416666667-825.824305555556-2353.7173611111
752835329280.559027777828149.45833333331131.10069444444-927.559027777766
763080530416.334027777828643.54166666671772.79236111111388.665972222225
773134831869.550694444429124.41666666672745.13402777778-521.550694444439
783455632991.317361111129654.8753336.442361111111564.68263888889
793385532401.129861111130328.58333333332072.546527777781453.87013888889
803478733538.225694444431184.83333333332353.392361111111248.77430555556
813252932427.875694444432108.3333333333319.542361111111101.124305555557
822999831307.575694444432921.6666666667-1614.09097222222-1309.57569444444
832925730687.017361111133731.3333333333-3044.31597222222-1430.01736111111
842815529659.721527777834563-4903.27847222222-1504.72152777778
853046632008.767361111135352.2083333333-3343.44097222222-1542.76736111111
863570435284.759027777836110.5833333333-825.824305555556419.240972222229
873932737816.267361111136685.16666666671131.100694444441510.73263888889
883935138982.667361111137209.8751772.79236111111368.332638888889
894223440476.925694444437731.79166666672745.134027777781757.07430555556
904363041495.734027777838159.29166666673336.442361111112134.26597222222
914372240627.338194444438554.79166666672072.546527777783094.66180555556
924312141231.642361111138878.252353.392361111111889.35763888890
933798539440.625694444439121.0833333333319.542361111111-1455.62569444444
943713537808.784027777839422.875-1614.09097222222-673.78402777778
953464636594.850694444439639.1666666667-3044.31597222222-1948.85069444445
963302634795.346527777839698.625-4903.27847222222-1769.34652777778
973508736406.767361111139750.2083333333-3343.44097222222-1319.76736111112
983884638964.384027777839790.2083333333-825.824305555556-118.384027777778
994201341209.309027777840078.20833333331131.10069444444803.690972222219
1004390842326.167361111140553.3751772.792361111111581.83263888890
1014286843874.050694444441128.91666666672745.13402777778-1006.05069444444
1024442344994.192361111141657.753336.44236111111-571.192361111105
1034416744197.463194444442124.91666666672072.54652777778-30.4631944444409
1044363645054.309027777842700.91666666672353.39236111111-1418.30902777778
1054438243410.375694444443090.8333333333319.542361111111971.62430555556
1064214241745.992361111143360.0833333333-1614.09097222222396.007638888892
1074345240744.434027777843788.75-3044.315972222222707.56597222223
1083691239286.804861111144190.0833333333-4903.27847222222-2374.80486111112
1094241341045.684027777844389.125-3343.440972222221367.31597222222
1104534443827.259027777844653.0833333333-825.8243055555561516.74097222222
1114487346140.975694444545009.8751131.10069444444-1267.97569444445
1124751047067.875694444445295.08333333331772.79236111111442.124305555561
1134955448031.384027777845286.252745.134027777781522.61597222223
1144736948570.650694444445234.20833333333336.44236111111-1201.65069444444
1154599847164.338194444445091.79166666672072.54652777778-1166.33819444444
1164814046875.684027777844522.29166666672353.392361111111264.31597222223
1174844144135.584027777843816.0416666667319.5423611111114305.41597222222
1184492841436.742361111143050.8333333333-1614.090972222223491.25763888888
1194045439117.934027777842162.25-3044.315972222221336.06597222223
1203866136423.888194444441327.1666666667-4903.278472222222237.11180555556
1213724637147.475694444440490.9166666667-3343.4409722222298.5243055555547
1223684338686.009027777839511.8333333333-825.824305555556-1843.00902777778
1233642439518.225694444438387.1251131.10069444444-3094.22569444445
1243759439143.292361111137370.51772.79236111111-1549.29236111110
1253814439426.217361111136681.08333333332745.13402777778-1282.21736111111
1263873739449.567361111136113.1253336.44236111111-712.567361111112
1273456037841.338194444435768.79166666672072.54652777778-3281.33819444444
1283608037996.184027777835642.79166666672353.39236111111-1916.18402777777
1293350835969.334027777835649.7916666667319.542361111111-2461.33402777778
1303546234062.700694444435676.7916666667-1614.090972222221399.29930555556
1313337432691.809027777835736.125-3044.31597222222682.190972222226
1323211031152.929861111136056.2083333333-4903.27847222222957.070138888892
13335533NA36696.3333333333NANA
13435532NA37403.25NANA
13537903NA38128.3333333333NANA
13636763NA38913.3333333333NANA
13740399NA39722.5416666667NANA
13844164NANANANA
13944496NANANANA
14043110NANANANA
14143880NANANANA
14243930NANANANA
14344327NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/13txu1293461465.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/13txu1293461465.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/2wkef1293461465.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/2wkef1293461465.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/3wkef1293461465.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/3wkef1293461465.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/47twi1293461465.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t12934613908orw2jy0mltk4dn/47twi1293461465.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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Software written by Ed van Stee & Patrick Wessa


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