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Toon Raeman - Opg.9 - Classical Deomposition Eigen reeks

R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 18 Aug 2008 04:33:16 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8.htm/, Retrieved Mon, 18 Aug 2008 10:34:30 +0000
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
12,11 11,42 11,71 12,04 12,21 12 12,36 12,32 12,96 12,79 13,19 12,34 13,25 12,54 12,77 12,96 13 13,61 13,8 14,16 14,27 14,69 15,01 15,09 15,14 14,2 13,83 14,31 14,04 14,9 14,92 15,36 15,5 15,65 16,18 15,44 15,58 15,24 15,33 16,07 15,82 15,87 15,72 17,07 16,83 17,52 17,76 17,36 17,95 16,71 17,14 16,72 17,26 17,24 17,69 18,13 18,08 18,18 18,18 17,64 17,89 16,82 16,61 16,66 17,02 16,91 17,18 18,06 17,58 17,48 17,54 17,44 17,79 16,79 16,19 16,62 16,39 16,54 17,26 18 17,29 18,16 17,82 17,48 18,31 17,04 17,03 16,97 17,11 17,12 17,69 18,5 18,27 18,45 18,35 18,03
 
Text written by user:
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
112.11NANA0.456111111111111NA
211.42NANA-0.500694444444445NA
311.71NANA-0.641875NA
412.04NANA-0.46423611111111NA
512.21NANA-0.502013888888888NA
612NANA-0.313194444444445NA
712.3612.200972222222212.335-0.1340277777777770.159027777777776
812.3212.930416666666712.42916666666670.501249999999999-0.610416666666666
912.9612.755416666666712.520.2354166666666650.204583333333336
1012.7913.135486111111112.60250.532986111111112-0.345486111111112
1113.1913.285347222222212.673750.611597222222222-0.0953472222222196
1212.3412.992430555555612.773750.218680555555556-0.652430555555556
1313.2513.356944444444412.90083333333330.456111111111111-0.106944444444446
1412.5412.536805555555613.0375-0.5006944444444450.0031944444444445
1512.7712.52687513.16875-0.6418750.243125000000001
1612.9612.838263888888913.3025-0.464236111111110.121736111111113
171312.955486111111113.4575-0.5020138888888880.0445138888888899
1813.6113.334722222222213.6479166666667-0.3131944444444450.275277777777779
1913.813.707222222222213.84125-0.1340277777777770.0927777777777745
2014.1614.490416666666713.98916666666670.501249999999999-0.330416666666668
2114.2714.337916666666714.10250.235416666666665-0.0679166666666671
2214.6914.735902777777814.20291666666670.532986111111112-0.0459027777777798
2315.0114.914097222222214.30250.6115972222222220.0959027777777788
2415.0914.618263888888914.39958333333330.2186805555555560.471736111111111
2515.1414.956111111111114.50.4561111111111110.183888888888891
2614.214.095972222222214.5966666666667-0.5006944444444450.104027777777778
2713.8314.056041666666714.6979166666667-0.641875-0.226041666666664
2814.3114.324930555555614.7891666666667-0.46423611111111-0.0149305555555532
2914.0414.375902777777814.8779166666667-0.502013888888888-0.335902777777777
3014.914.628055555555614.94125-0.3131944444444450.271944444444445
3114.9214.840138888888914.9741666666667-0.1340277777777770.079861111111109
3215.3615.537083333333315.03583333333330.501249999999999-0.177083333333334
3315.515.377083333333315.14166666666670.2354166666666650.122916666666667
3415.6515.810486111111115.27750.532986111111112-0.160486111111112
3516.1816.036597222222215.4250.6115972222222220.143402777777776
3615.4415.758263888888915.53958333333330.218680555555556-0.318263888888890
3715.5816.069444444444415.61333333333330.456111111111111-0.489444444444443
3815.2415.217222222222215.7179166666667-0.5006944444444450.0227777777777778
3915.3315.202708333333315.8445833333333-0.6418750.127291666666666
4016.0715.513680555555615.9779166666667-0.464236111111110.556319444444442
4115.8215.619652777777816.1216666666667-0.5020138888888880.20034722222222
4215.8715.954305555555616.2675-0.313194444444445-0.0843055555555559
4315.7216.312222222222216.44625-0.134027777777777-0.592222222222222
4417.0717.107516.606250.501249999999999-0.0375000000000014
4516.8316.978333333333316.74291666666670.235416666666665-0.148333333333333
4617.5217.378402777777816.84541666666670.5329861111111120.141597222222227
4717.7617.544097222222216.93250.6115972222222220.215902777777778
4817.3617.268263888888917.04958333333330.2186805555555560.0917361111111106
4917.9517.644861111111117.188750.4561111111111110.305138888888887
5016.7116.814305555555617.315-0.500694444444445-0.104305555555555
5117.1416.76937517.41125-0.6418750.370624999999997
5216.7217.026597222222217.4908333333333-0.46423611111111-0.306597222222223
5317.2617.033819444444417.5358333333333-0.5020138888888880.226180555555562
5417.2417.251805555555517.565-0.313194444444445-0.0118055555555507
5517.6917.440138888888917.5741666666667-0.1340277777777770.249861111111120
5618.1318.077517.576250.5012499999999990.0525000000000055
5718.0817.794166666666717.558750.2354166666666650.285833333333333
5818.1818.067152777777817.53416666666670.5329861111111120.112847222222225
5918.1818.133263888888917.52166666666670.6115972222222220.0467361111111124
6017.6417.716597222222217.49791666666670.218680555555556-0.0765972222222224
6117.8917.919027777777817.46291666666670.456111111111111-0.0290277777777774
6216.8216.938055555555617.43875-0.500694444444445-0.118055555555554
6316.6116.77312517.415-0.641875-0.163125000000004
6416.6616.900763888888917.365-0.46423611111111-0.240763888888893
6517.0216.807152777777817.3091666666667-0.5020138888888880.212847222222223
6616.9116.960972222222217.2741666666667-0.313194444444445-0.0509722222222244
6717.1817.127638888888917.2616666666667-0.1340277777777770.0523611111111109
6818.0617.757517.256250.5012499999999990.302500000000002
6917.5817.472916666666717.23750.2354166666666650.107083333333335
7017.4817.751319444444417.21833333333330.532986111111112-0.271319444444444
7117.5417.802013888888917.19041666666670.611597222222222-0.262013888888891
7217.4417.367430555555617.148750.2186805555555560.0725694444444436
7317.7917.592777777777817.13666666666670.4561111111111110.197222222222226
7416.7916.636805555555617.1375-0.5006944444444450.153194444444445
7516.1916.481041666666717.1229166666667-0.641875-0.291041666666661
7616.6216.674930555555617.1391666666667-0.46423611111111-0.0549305555555542
7716.3916.677152777777817.1791666666667-0.502013888888888-0.287152777777777
7816.5416.879305555555617.1925-0.313194444444445-0.339305555555555
7917.2617.081805555555617.2158333333333-0.1340277777777770.178194444444447
801817.749166666666717.24791666666670.5012499999999990.250833333333336
8117.2917.5287517.29333333333330.235416666666665-0.238750000000000
8218.1617.875902777777817.34291666666670.5329861111111120.284097222222222
8317.8217.999097222222217.38750.611597222222222-0.179097222222222
8417.4817.660347222222217.44166666666670.218680555555556-0.180347222222224
8518.3117.939861111111117.483750.4561111111111110.370138888888889
8617.0417.021805555555617.5225-0.5006944444444450.0181944444444433
8717.0316.942291666666717.5841666666667-0.6418750.0877083333333353
8816.9717.172847222222217.6370833333333-0.46423611111111-0.202847222222228
8917.1117.169236111111117.67125-0.502013888888888-0.0592361111111082
9017.1217.403055555555617.71625-0.313194444444445-0.283055555555553
9117.69NANA-0.134027777777777NA
9218.5NANA0.501249999999999NA
9318.27NANA0.235416666666665NA
9418.45NANA0.532986111111112NA
9518.35NANA0.611597222222222NA
9618.03NANA0.218680555555556NA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/1paj91219055589.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/1paj91219055589.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/24axd1219055589.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/24axd1219055589.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/3m1wq1219055589.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/3m1wq1219055589.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/4v3if1219055589.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/18/t1219055670i0etef7uxe1a9h8/4v3if1219055589.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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