Home » date » 2009 » Jun » 01 »

Datareeks - Aardolie - Silke van den Berg

*Unverified author*
R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 01 Jun 2009 09:17:53 -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/01/t1243869502j71yan5a6ygnast.htm/, Retrieved Mon, 01 Jun 2009 17:18:22 +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/01/t1243869502j71yan5a6ygnast.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 «
493395,00 487190,00 519493,00 519453,00 538588,00 438224,00 542034,00 512027,00 619880,00 533737,00 573789,00 589213,00 532168,00 551102,00 593789,00 527106,00 547327,00 601305,00 610872,00 601325,00 642143,00 614216,00 657979,00 673098,00 602297,00 615381,00 703671,00 733852,00 716596,00 745798,00 742027,10 679181,20 739022,70 645410,60 729382,10 671052,70 744954,80 677639,30 778207,20 763316,20 658531,60 831700,10 664156,30 621402,10 683588,70 600023,80 643273,80 653615,90 620177,50 574128,80 599828,00 599369,40 596617,70 616114,60 510226,90 493960,10 634503,30 588556,20 603239,00 617458,20 646543,50 680125,60 731595,80 759600,30 785031,70 849573,30 762342,00 815346,60 929603,20 784057,50 944667,70 1007258,30 664292,70 873207,40 1146510,00 1417266,80 1089387,90 1373379,70 1009397,60 818175,10 1003458,10 961142,70 1121906,60 1141713,30 1042352,60 992223,60 920525,30 1076093,40 967880,40 1236416,10
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1493395NANA-69760.6998842592NA
2487190NANA-48273.8755787037NA
3519493NANA43939.1758101852NA
4519453NANA79458.9605324074NA
5538588NANA4848.02650462962NA
6438224NANA101267.979976852NA
7542034506280.882060185532200.791666667-25919.909606481535753.1179398148
8512027459014.497337963536479.333333333-77464.835995370453012.5026620372
9619880559928.96747685254223817690.967476851859951.0325231482
10533737484110.061226852545652.541666667-61542.480439814849626.9387731482
11573789562567.03900463546335.54166666716231.497337963011221.9609953704
12589213573019.902199074553494.70833333319525.193865740816193.0978009258
13532168493397.300115741563158-69760.699884259238770.6998842594
14551102521473.124421296569747-48273.875578703729628.8755787037
15593789618334.550810185574395.37543939.1758101852-24545.5508101851
16527106658135.252199074578676.29166666779458.9605324074-131029.252199074
17547327590385.52650463585537.54848.02650462962-43058.5265046296
18601305693808.604976852592540.625101267.979976852-92503.6049768518
19610872573037.965393518598957.875-25919.909606481537834.0346064816
20601325527093.372337963604558.208333333-77464.835995370474231.6276620372
21642143629505.884143519611814.91666666717690.967476851812637.1158564815
22614216563465.269560185625007.75-61542.480439814850750.7304398147
23657979656906.53900463640675.04166666716231.49733796301072.46099537041
24673098673273.652199074653748.45833333319525.1938657408-175.652199074044
25602297595473.095949074665233.795833333-69760.69988425926823.9040509261
26615381625668.724421296673942.6-48273.8755787037-10287.7244212963
27703671725162.438310185681223.262543939.1758101852-21491.4383101852
28733852766018.652199074686559.69166666779458.9605324074-32166.6521990740
29716596695682.622337963690834.5958333334848.0265046296220913.3776620372
30745798794992.484143518693724.504166667101267.979976852-49194.4841435184
31742027.1673663.448726852699583.358333333-25919.909606481568363.6512731481
32679181.2630656.693171296708121.529166667-77464.835995370448524.5068287037
33739022.7731512.267476852713821.317690.96747685187510.43252314813
34645410.6656612.169560185718154.65-61542.4804398148-11201.5695601852
35729382.1733194.472337963716962.97516231.4973379630-3812.37233796297
36671052.7737648.073032407718122.87916666719525.1938657408-66595.3730324075
37744954.8648696.816782407718457.516666667-69760.699884259296257.9832175927
38677639.3664531.561921296712805.4375-48273.875578703713107.7380787039
39778207.2752027.400810185708088.22543939.175810185226179.7991898148
40763316.2783346.31886574703887.35833333379458.9605324074-20030.1188657407
41658531.6703256.422337963698408.3958333334848.02650462962-44724.8223379629
42831700.1795361.996643518694094.016666667101267.97997685236338.1033564815
43664156.3662248.519560185688168.429166667-25919.90960648151907.78043981479
44621402.1601191.60150463678656.4375-77464.835995370420210.4984953704
45683588.7684602.000810185666911.03333333317690.9674768518-1013.30081018514
46600023.8591104.969560185652647.45-61542.48043981488918.83043981495
47643273.8659468.084837963643236.587516231.4973379630-16194.2848379629
48653615.9651199.306365741631674.112519525.19386574082416.59363425930
49620177.5546516.958449074616277.658333333-69760.699884259273660.541550926
50574128.8556279.974421296604553.85-48273.875578703717848.8255787038
51599828641137.717476852597198.54166666743939.1758101852-41309.7174768519
52599369.4674134.460532407594675.579458.9605324074-74765.0605324074
53596617.7597377.593171296592529.5666666674848.02650462962-759.893171296222
54616114.6690622.859143518589354.879166667101267.979976852-74508.2591435185
55510226.9563026.982060185588946.891666667-25919.9096064815-52800.0820601851
56493960.1516997.172337963594462.008333333-77464.8359953704-23037.0723379629
57634503.3622059.834143518604368.86666666717690.967476851812443.4658564817
58588556.2554992.998726852616535.479166667-61542.480439814833563.2012731482
59603239647293.847337963631062.3516231.4973379630-44054.8473379629
60617458.2668165.573032407648640.37916666719525.1938657408-50707.3730324074
61646543.5599111.920949074668872.620833333-69760.699884259247431.5790509258
62680125.6644494.64525463692768.520833333-48273.875578703735630.9547453705
63731595.8762394.629976852718455.45416666643939.1758101852-30798.8299768516
64759600.3818356.13136574738897.17083333379458.9605324074-58755.8313657406
65785031.7766117.280671296761269.2541666674848.0265046296218914.4193287037
66849573.3893005.100810185791737.120833333101267.979976852-43431.8008101851
67762342782798.432060185808718.341666667-25919.9096064815-20456.4320601851
68815346.6740038.130671296817502.966666667-77464.835995370475308.4693287038
69929603.2860527.100810185842836.13333333317690.967476851869076.0991898148
70784057.5825984.515393518887526.995833333-61542.4804398148-41927.0153935184
71944667.7943842.772337963927611.27516231.4973379630824.92766203708
721007258.3981643.24386574962118.0519525.193865740825615.0561342594
73664292.7924476.60011574994237.3-69760.6998842592-260183.900115741
74873207.4956375.2619212961004649.1375-48273.8755787037-83167.8619212962
7511465101051783.454976851007844.2791666743939.175810185294726.5450231482
761417266.81097759.077199071018300.1166666779458.9605324074319507.722800926
771089387.91037911.647337961033063.620833334848.0265046296251476.2526620372
781373379.71147318.846643521046050.86666667101267.979976852226060.853356482
791009397.61041485.744560191067405.65416667-25919.9096064815-32088.1445601851
80818175.11010652.322337961088117.15833333-77464.8359953704-192477.222337963
811003458.11101351.104976851083660.137517690.9674768518-97893.0049768515
82961142.7998486.0695601851060028.55-61542.4804398148-37343.369560185
831121906.61056981.676504631040750.1791666716231.497337963064924.9234953705
841141713.31049505.743865741029980.5519525.193865740892207.5561342592
851042352.6NANANANA
86992223.6NANANANA
87920525.3NANANANA
881076093.4NANANANA
89967880.4NANANANA
901236416.1NANANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/1aecp1243869468.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/1aecp1243869468.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/262of1243869468.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/262of1243869468.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/3y4xe1243869468.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/3y4xe1243869468.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/4kpcu1243869468.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869502j71yan5a6ygnast/4kpcu1243869468.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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