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cd hoog geschoold

*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: Tue, 21 Dec 2010 19:15:16 +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/21/t1292958830i60ljb5abhmtmzo.htm/, Retrieved Tue, 21 Dec 2010 20:13:51 +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/21/t1292958830i60ljb5abhmtmzo.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 «
19246 17549 16428 16209 15235 16186 24971 30776 26416 23157 20155 19790 18849 17573 16597 16158 15507 16433 26325 31144 30535 27596 24064 23854 22407 21125 20226 19547 18933 20372 34331 37329 36761 32737 29321 28883 27436 25101 23776 23782 23027 25606 41328 44751 42855 37628 33544 33275 32009 30813 29143 28121 27007 29112 44067 48481 46581 41166 36824 35936 33633 31630 30434 28546 27660 29830 45599 49303 44417 40386 35544 35019 30400 29602 27701 27937 27283 29372 42821 45386 40170 34371 30077 29251 27202 25714 23784 22968 22243 24255 37282 38794 31828 27949 24605 25695 23338 21941 22034 20637 19418 22454 33261 34995 29132 26171 23828 25743 25204 25679 25281 25136 24794 28278 40062 42590 37885 34061 32412 34647 31750 31288 29331 28768 27780 30113 41240 43271 38108 34382 31551
 
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'RServer@AstonUniversity' @ vre.aston.ac.uk


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
119246NANA0.91387218069808NA
217549NANA0.865844319530166NA
316428NANA0.824527617125806NA
416209NANA0.79776183517912NA
515235NANA0.767986530518108NA
616186NANA0.838681312320585NA
72497126224.848336257120493.29166666671.279679651410670.9521885381307
83077628227.963309226520477.751.37846996419171.09026640225016
92641625634.7763068620485.79166666671.25134418644761.03047515155929
102315722679.642711442420490.70833333331.106825705705261.02104783107173
112015520195.210489081220499.91666666670.9851362235983660.998008909632165
121979020313.668161906620521.54166666670.9898704732745440.974220896111288
131884918815.028924257220588.250.913872180698081.00180552875467
141757317888.3436414932206600.8658443195301660.98237155726583
151659717188.892878904320846.95833333330.8245276171258060.96556538672536
161615816915.37631229721203.54166666670.797761835179120.955225571201371
171550716551.165714144721551.3750.7679865305181080.936912859663272
181643318353.352388276921883.58333333330.8386813123205850.895367759107405
192632528410.381220910122201.16666666671.279679651410670.92659791487151
203114431012.013146905722497.41666666671.37846996419171.00425599113702
213053528526.42416437622796.6251.25134418644761.07041106253101
222759625555.544836766523089.04166666671.106825705705261.07984393118075
232406423025.5889541646233730.9851362235983661.04509813181771
242385423440.00907333223679.8750.9898704732745441.01766172211678
252240722095.220804842924177.58333333330.913872180698081.01411070737473
262112521445.989719902724768.8750.8658443195301660.98503264600538
272022620849.0053266431252860.8245276171258060.97011822305753
281954720550.04571352625759.6250.797761835179120.95119009818719
291893320115.775195544526192.8750.7679865305181080.941201609977902
302037222326.919610887826621.45833333330.8386813123205850.91244114078619
313433134603.230933955627040.54166666671.279679651410670.992132788568929
323732937791.787920788527415.751.37846996419170.987754272918802
333676134698.940060734327729.33333333331.25134418644761.05942717373085
343273731050.565523691328053.70833333331.106825705705261.05431252049248
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372743626775.579100280629299.04166666670.913872180698081.02466504635608
382510125888.600846565429899.83333333330.8658443195301660.969577311217656
392377625117.5848005034304630.8245276171258060.946587826371087
402378224667.361025038330920.70833333330.797761835179120.964107995819267
412302724038.330399043231300.45833333330.7679865305181080.957928425882544
422560626552.161117304231659.41666666670.8386813123205850.964365946970412
434132840991.924953652432032.95833333331.279679651410671.00819856707699
444475144747.202742608732461.51.37846996419171.00008486021826
454285541198.161068437632923.1251.25134418644761.04021633220012
463762836887.779824629933327.54166666671.106825705705261.02006681288191
473354433173.64138282233674.16666666670.9851362235983661.01116424371097
483327533641.820393914833986.08333333330.9898704732745440.989096297714582
493200931296.733246239234246.29166666670.913872180698081.02275850160324
503081329885.338225516634515.83333333330.8658443195301661.03104069853529
512914328715.411057831934826.50.8245276171258061.01489057361244
522812128024.708468313235129.16666666670.797761835179121.00343595123552
532700727196.899001870435413.250.7679865305181080.993017623007046
542911229908.03955339135660.79166666670.8386813123205850.973383760176928
554406745862.865586790735839.33333333331.279679651410670.960842708718403
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574658145084.523275497236028.8751.25134418644761.03319269265327
584116639956.823035599636100.3751.106825705705261.03026208973929
593682435608.036133361536145.29166666670.9851362235983661.03414857989035
603593635835.703319515636202.41666666670.9898704732745441.00279879202007
613363333170.056982647636296.16666666670.913872180698081.01395665426787
623163031511.754626060836394.250.8658443195301661.00375242113118
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642854628891.476702235336215.66666666670.797761835179120.98804226222855
652766027747.225349864136129.83333333330.7679865305181080.996856429831656
662983030224.64174879236038.29166666670.8386813123205850.98694304627092
674559945896.190577712835865.3751.279679651410670.99352472233595
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694441744357.38802448935447.79166666671.25134418644761.00134390184287
704038639080.40154763235308.54166666671.106825705705261.03340801017044
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733040032074.933486111135097.83333333330.913872180698080.947780609215094
742960230147.725131180934818.8750.8658443195301660.981898298169884
752770128428.64722365934478.70833333330.8245276171258060.974404437258856
762793727164.687969913634051.1250.797761835179121.02843073444988
772728325783.38779301333572.70833333330.7679865305181081.0581619536977
782937227764.195393826233104.58333333330.8386813123205851.05790928148169
794282141885.1946703225327311.279679651410671.02234215065832
804538644711.707141030832435.751.37846996419171.01508090167173
814017040181.339638266732110.54166666671.25134418644760.999717788446856
823437135130.970723249231740.29166666671.106825705705260.97836750002623
833007730857.668215827531323.250.9851362235983660.974700997808152
842925130587.038868786530900.04166666670.9898704732745440.9563200977212
852720227832.929213348330456.04166666670.913872180698080.977331555420848
862571425932.542445781529950.58333333330.8658443195301660.99157265639347
872378424182.020797604729328.33333333330.8245276171258060.983540631242691
882296822906.26853380428713.16666666670.797761835179121.00269495950879
892224321670.723923772228217.58333333330.7679865305181081.02640779690797
902425523350.075866864227841.41666666670.8386813123205851.03875465494397
913728235232.460082551327532.251.279679651410671.05817192193354
923879437513.739041761327214.04166666671.37846996419171.03412778867
933182833766.167248419826983.91666666671.25134418644760.942600318414566
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952460526203.679458835626599.04166666670.9851362235983660.938990268090135
962569526138.80842950926406.29166666670.9898704732745440.983021091772188
972333823910.285189731926163.70833333330.913872180698080.976065313098916
982194122371.577297480525837.8750.8658443195301660.980753377745565
992203421080.903718959825567.250.8245276171258061.0452113578121
1002063720247.860178375425380.83333333330.797761835179121.01921881217059
1011941819410.379567263625274.3750.7679865305181081.00039259576094
1022245421171.6710482208252440.8386813123205851.06056815018798
1033326132406.287572410925323.751.279679651410671.02637489486197
1043499535229.901492338225557.251.37846996419170.993332326166472
1052913232345.109506685325848.29166666671.25134418644760.900661659345406
1062617128966.781661750226171.04166666671.106825705705260.903483179650506
1072382826187.383663803626582.50.9851362235983660.909903803522582
1082574326775.171410015427049.16666666670.9898704732745440.96145042755434
1092520425200.215772787227575.20833333330.913872180698081.00015016646075
1102567924395.199779609128175.04166666670.8658443195301661.05262511608796
1112528123792.740696369228856.20833333330.8245276171258061.06255098236152
1122513623573.596308931329549.66666666670.797761835179121.06627769775105
1132479423220.90473562330236.08333333330.7679865305181081.06774478782318
1142827825969.557165678830964.750.8386813123205851.08889034262671
1154006240448.754261614131608.51.279679651410670.990438413526592
1164259044269.505463767832114.95833333331.37846996419170.962061797479477
1173788540690.480304127632517.41666666671.25134418644760.931053153387255
1183406136345.389111096632837.51.106825705705260.937147760225818
1193241232621.062056068633113.250.9851362235983660.993591194066298
1203464732976.668680477333314.1250.9898704732745441.05065191198381
12131750NA33439.6666666667NANA
12231288NA33517.125NANA
12329331NA33554.7916666667NANA
12428768NA33577.4583333333NANA
12527780NA33554.9583333333NANA
12630113NANANANA
12741240NANANANA
12843271NANANANA
12938108NANANANA
13034382NANANANA
13131551NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/1ulj21292958912.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/1ulj21292958912.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/2ulj21292958912.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/2ulj21292958912.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/3mu0n1292958912.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/3mu0n1292958912.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/4mu0n1292958912.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292958830i60ljb5abhmtmzo/4mu0n1292958912.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')
 




Copyright

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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