Home » date » 2011 » May » 15 »

marina cabraja mar205 opgave 9.1 classical decomposition inschrijving personenwagens

*Unverified author*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Sun, 15 May 2011 14:42:30 +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/15/t1305470528h0eu1s2c2hjr8jo.htm/, Retrieved Sun, 15 May 2011 16:42:12 +0200
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W91
 
Dataseries X:
» Textbox « » Textfile « » CSV «
112 118 132 129 121 135 148 148 136 119 104 118 115 126 41086 39690 43129 37863 35953 29133 24693 22205 21725 27192 21790 13253 37702 30364 32609 30212 29965 28352 25814 22414 20506 28806 22228 13971 36845 35338 35022 34777 26887 23970 22780 17351 21382 24561 17409 11514 31514 27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1112NANA-7308.15104166667NA
2118NANA-12682.1579861111NA
3132NANA9790.55034722222NA
4129NANA6623.79340277778NA
5121NANA9411.74479166667NA
6135NANA6092.02951388889NA
71481423.55034722222126.7916666666671296.75868055556-1275.55034722222
8148618.897569444445127.25491.647569444445-470.897569444445
9136-1252.588541666671834-3086.588541666671388.58854166667
10119-287.8593750000035188.79166666667-5476.65104166667406.859375000003
111044252.585069444458629.16666666667-4376.58159722222-4148.58506944445
1211811216.772569444411993.1666666667-776.394097222222-11098.7725694444
131157748.89062515057.0416666667-7308.15104166667-7633.890625
141265074.4670138888917756.625-12682.1579861111-4948.46701388889
154108629778.092013888919987.54166666679790.5503472222211307.9079861111
163969028554.7934027778219316623.7934027777811135.2065972222
174312933163.869791666723752.1259411.744791666679965.13020833334
183786331873.112847222225781.08333333336092.029513888895989.88715277778
193595329109.050347222227812.29166666671296.758680555566843.94965277778
202913329754.022569444429262.375491.647569444445-621.022569444442
212469326581.744791666729668.3333333333-3086.58854166667-1888.74479166666
222220523662.098958333329138.75-5476.65104166667-1457.09895833333
232172523935.251736111128311.8333333333-4376.58159722222-2210.25173611111
242719226778.314236111127554.7083333333-776.394097222222413.685763888891
252179019678.26562526986.4166666667-7308.151041666672111.734375
261325314022.217013888926704.375-12682.1579861111-769.21701388889
273770236509.092013888926718.54166666679790.550347222221192.90798611111
283036433397.751736111126773.95833333336623.79340277778-3033.75173611111
293260936143.619791666726731.8759411.74479166667-3534.61979166666
303021232840.362847222226748.33333333336092.02951388889-2628.36284722222
312996528130.592013888926833.83333333331296.758680555561834.40798611111
322835227373.647569444426882491.647569444445978.352430555558
332581423789.619791666726876.2083333333-3086.588541666672024.38020833333
342241421571.098958333327047.75-5476.65104166667842.901041666664
352050622978.960069444427355.5416666667-4376.58159722222-2472.96006944445
362880626869.897569444427646.2916666667-776.3940972222221936.10243055556
372222820400.098958333327708.25-7308.151041666671827.90104166667
381397114715.258680555627397.4166666667-12682.1579861111-744.258680555555
393684536878.967013888927088.41666666679790.55034722222-33.9670138888796
403533833374.835069444426751.04166666676623.793402777781963.16493055555
413502235988.32812526576.58333333339411.74479166667-966.328125
423477732528.237847222226436.20833333336092.029513888892248.76215277778
432688727355.300347222226058.54166666671296.75868055556-468.300347222219
442397026247.022569444425755.375491.647569444445-2277.02256944445
452278022344.286458333325430.875-3086.58854166667435.713541666672
461735119387.64062524864.2916666667-5476.65104166667-2036.640625
472138219911.585069444424288.1666666667-4376.581597222221470.41493055556
482456122918.772569444423695.1666666667-776.3940972222221642.22743055556
491740915838.598958333323146.75-7308.151041666671570.40104166667
501151410272.217013888922954.375-12682.15798611111241.78298611111
513151432694.842013888922904.29166666679790.55034722222-1180.84201388889
522707129514.043402777822890.256623.79340277778-2443.04340277777
532946232306.994791666722895.259411.74479166667-2844.99479166667
542610528992.987847222222900.95833333336092.02951388889-2887.98784722222
552239724241.467013888922944.70833333331296.75868055556-1844.46701388889
562384323616.730902777823125.0833333333491.647569444445226.269097222223
572170520061.369791666723147.9583333333-3086.588541666671643.63020833334
581808917622.432291666723099.0833333333-5476.65104166667466.567708333336
592076419109.501736111123486.0833333333-4376.581597222221654.49826388889
602531623247.397569444424023.7916666667-776.3940972222222068.60243055555
611770416974.432291666724282.5833333333-7308.15104166667729.567708333336
621554811632.008680555624314.1666666667-12682.15798611113915.99131944445
632802933970.342013888924179.79166666679790.55034722222-5941.34201388889
642938330626.376736111124002.58333333336623.79340277778-1243.37673611111
653643833374.7447916667239639411.744791666673063.25520833333
663203429932.862847222223840.83333333336092.029513888892101.13715277778
672267925093.050347222223796.29166666671296.75868055556-2414.05034722222
682431924276.439236111123784.7916666667491.64756944444542.5607638888905
691800420697.07812523783.6666666667-3086.58854166667-2693.078125
701753718220.432291666723697.0833333333-5476.65104166667-683.432291666668
712036618856.585069444423233.1666666667-4376.581597222221509.41493055556
722278221919.522569444422695.9166666667-776.394097222222862.477430555558
731916915145.01562522453.1666666667-7308.151041666674023.984375
74138079873.1336805555622555.2916666667-12682.15798611113933.86631944444
752974332457.967013888922667.41666666679790.55034722222-2714.96701388889
762559129339.501736111122715.70833333336623.79340277778-3748.50173611111
772909632148.7447916667227379411.74479166667-3052.74479166666
782648228675.737847222222583.70833333336092.02951388889-2193.73784722222
792240523726.842013888922430.08333333331296.75868055556-1321.84201388888
802704422763.439236111122271.7916666667491.6475694444454280.56076388889
8117970NANA-3086.58854166667NA
8218730NANA-5476.65104166667NA
8319684NANA-4376.58159722222NA
8419785NANA-776.394097222222NA
8518479NANANANA
8610698NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/1mwci1305470546.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/1mwci1305470546.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/2uf1v1305470546.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/2uf1v1305470546.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/3wr4k1305470546.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/3wr4k1305470546.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/4i2z41305470546.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/15/t1305470528h0eu1s2c2hjr8jo/4i2z41305470546.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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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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