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*Unverified author*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 16 May 2011 21:11:51 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f.htm/, Retrieved Mon, 16 May 2011 23:07:55 +0200
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W92
 
Dataseries X:
» Textbox « » Textfile « » CSV «
30790 30800 31025 30835 31110 31270 31090 30755 31460 32135 32680 32700 32515 32275 32200 31835 31985 31875 31795 32260 33255 33160 32195 33130 33950 34210 33855 33735 34175 34265 33915 33660 33720 33810 33590 33545 33660 33165 33800 33880 33975 33930 33905 33890 33640 34395 34245 33940 34295 33745 33535 33715 33600 34120 34330 34130 33755 32910 32910 32850 32780 32565 31905 31975 31380 31355 31440 30310 31410 31300 31070 31075 31815
 
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' @ 216.218.223.82


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
130790NANA1.00897888286911NA
230800NANA1.00157741743535NA
331025NANA0.99757658076116NA
430835NANA0.996811130683288NA
531110NANA0.997128329263887NA
631270NANA1.00048141575802NA
73109031464.995141340331459.3751.000178647584080.98808214844287
83075531535.531132155631592.70833333330.9981901772847560.975249152174269
93146031638.297090709431703.1250.9979551571243970.9943645168323
103213531827.546058052831793.751.00106297803981.00965999519367
113268031770.25365691431871.8750.996811566841111.02863516145985
123270032037.252752212131933.54166666671.003247716355051.02068676902211
133251532275.342627577531988.1251.008978882869111.00742540134083
143227532130.812213288132080.20833333331.001577417435351.0044875238682
153220032139.63131912732217.70833333330.997576580761161.00187832524504
163183532232.095579629732335.20833333330.9968111306832880.98768011907111
173198532264.787649224832357.70833333330.9971283292638870.991328390186025
183187532370.993074107232355.41666666671.000481415758020.984677854245258
193179532438.919099425332433.1251.000178647584080.980149797918615
203226032514.589331042432573.54166666670.9981901772847560.99216999702963
213325532656.211350976332723.1250.9979551571243971.01833613344145
223316032906.191416890732871.251.00106297803981.0077130950797
233219532936.315521041733041.66666666670.996811566841110.977492457510372
243313033340.429733769133232.51.003247716355050.993688451665157
253395033720.494673353633420.41666666671.008978882869111.00680610794324
263421033620.032635837333567.08333333331.001577417435351.01754809016853
273385533563.256231254933644.79166666670.997576580761161.00869235591252
283373533583.813006633333691.250.9968111306832881.00450178165704
293417533679.46346636833776.45833333330.9971283292638871.0147133143652
303426533868.171826063433851.8751.000481415758021.01171684660083
313391533863.131819474733857.08333333331.000178647584081.00153170063542
323366033740.283686233333801.45833333330.9981901772847560.997620539086752
333372033686.600050707233755.6250.9979551571243971.00099149065927
343381033795.260474262333759.3751.00106297803981.00043614180009
353359033649.451129485933757.08333333330.996811566841110.998233221419954
363354533844.352701296633734.79166666671.003247716355050.991155017679355
373366034023.188338214333720.41666666671.008978882869110.989325270324346
383316533782.788966170633729.58333333331.001577417435350.981712908108647
393380033654.07726579533735.83333333330.997576580761161.00433596003992
403388033649.228737084433756.8750.9968111306832881.00685814420053
413397533711.454666931833808.54166666670.9971283292638871.00781767905515
423393033868.5886933233852.29166666671.000481415758021.00181322307924
433390533901.263630413833895.20833333331.000178647584081.0001102132837
443389033884.397393078833945.83333333330.9981901772847561.0001653447413
453364033889.517599322533958.95833333330.9979551571243970.992637322186978
463439533977.120248606233941.04166666671.00106297803981.01229885724088
473424533810.394663715433918.54166666670.996811566841111.01285419293703
483394034020.966101363333910.83333333331.003247716355050.997620111635805
493429534241.169817700833936.45833333331.008978882869111.00157208946382
503374534017.742335343933964.16666666671.001577417435350.991982350484778
513353533896.613071992633978.95833333330.997576580761160.989331881883758
523371533813.702573647233921.8750.9968111306832880.997080988885137
533360033707.299965559933804.3750.9971283292638870.996816714312047
543412033719.558649097733703.33333333331.000481415758021.01187564033888
553433033600.793295035533594.79166666671.000178647584081.02170206811969
563413033421.902610936833482.50.9981901772847561.02118662714406
573375533297.189632104333365.41666666670.9979551571243971.01374921946729
583291033260.3174453723332251.00106297803980.989467405236055
593291032954.5903997671330600.996811566841110.998646913852482
603285032958.986591613332852.29166666671.003247716355050.996693266302034
613278032909.527896247532616.66666666671.008978882869110.996064121714056
623256532388.092412391832337.08333333331.001577417435351.00546211815613
633190532002.464539272332080.20833333330.997576580761160.99695446770505
643197531813.642573728331915.41666666670.9968111306832881.00507195697248
653138031680.428901262531771.66666666670.9971283292638870.990516892867871
663135531636.264534409931621.04166666671.000481415758020.991109426522086
673144031512.503627100531506.8751.000178647584080.997699210828866
6830310NANA0.998190177284756NA
6931410NANA0.997955157124397NA
7031300NANA1.0010629780398NA
7131070NANA0.99681156684111NA
7231075NANA1.00324771635505NA
7331815NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/187gm1305580307.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/187gm1305580307.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/2mbhj1305580307.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/2mbhj1305580307.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/39emt1305580307.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/39emt1305580307.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/46alz1305580307.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/16/t1305580069g1ojfunb4sxxh1f/46alz1305580307.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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