Home » date » 2009 » Aug » 18 »

Opgave 9 - Robbert Van Hees

*Unverified author*
R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Tue, 18 Aug 2009 03:48:34 -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/Aug/18/t1250589122irmufisq66eytru.htm/, Retrieved Tue, 18 Aug 2009 11:52:08 +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/Aug/18/t1250589122irmufisq66eytru.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 «
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 18.49 18.07 17.8 17.88 18.12 18.68 18.8 19.64 19.56 19.3 20.07 19.82 20.29 19.36 18.74 18.87 18.87 18.91 19.31 20.06 20.72 20.42 20.58 20.58 21.18 19.87 19.83 19.48 19.49 19.4 19.89 20.44 20.07 19.75 19.54 19.07
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
112.11NANA0.584180555555554NA
211.42NANA-0.404027777777779NA
311.71NANA-0.604486111111112NA
412.04NANA-0.536111111111112NA
512.21NANA-0.533569444444444NA
612NANA-0.382069444444444NA
712.3612.196763888888912.335-0.1382361111111100.163236111111111
812.3212.874930555555612.42916666666670.445763888888889-0.554930555555556
912.9612.872722222222212.520.3527222222222210.0872777777777802
1012.7913.048388888888912.60250.44588888888889-0.258388888888891
1113.1913.262305555555612.673750.588555555555556-0.0723055555555554
1212.3412.955138888888912.773750.181388888888890-0.61513888888889
1313.2513.485013888888912.90083333333330.584180555555554-0.23501388888889
1412.5412.633472222222213.0375-0.404027777777779-0.0934722222222213
1512.7712.564263888888913.16875-0.6044861111111120.205736111111111
1612.9612.766388888888913.3025-0.5361111111111120.193611111111114
171312.923930555555613.4575-0.5335694444444440.0760694444444461
1813.6113.265847222222213.6479166666667-0.3820694444444440.344152777777778
1913.813.703013888888913.84125-0.1382361111111100.096986111111109
2014.1614.434930555555613.98916666666670.445763888888889-0.274930555555558
2114.2714.455222222222214.10250.352722222222221-0.185222222222222
2214.6914.648805555555614.20291666666670.445888888888890.041194444444443
2315.0114.891055555555614.30250.5885555555555560.118944444444443
2415.0914.580972222222214.39958333333330.1813888888888900.509027777777778
2515.1415.084180555555614.50.5841805555555540.0558194444444471
2614.214.192638888888914.5966666666667-0.4040277777777790.0073611111111127
2713.8314.093430555555614.6979166666667-0.604486111111112-0.263430555555553
2814.3114.253055555555614.7891666666667-0.5361111111111120.0569444444444471
2914.0414.344347222222214.8779166666667-0.533569444444444-0.304347222222221
3014.914.559180555555614.94125-0.3820694444444440.340819444444444
3114.9214.835930555555614.9741666666667-0.1382361111111100.0840694444444434
3215.3615.481597222222215.03583333333330.445763888888889-0.121597222222224
3315.515.494388888888915.14166666666670.3527222222222210.00561111111111146
3415.6515.723388888888915.27750.44588888888889-0.0733888888888892
3516.1816.013555555555615.4250.5885555555555560.166444444444442
3615.4415.720972222222215.53958333333330.181388888888890-0.280972222222223
3715.5816.197513888888915.61333333333330.584180555555554-0.617513888888887
3815.2415.313888888888915.7179166666667-0.404027777777779-0.073888888888888
3915.3315.240097222222215.8445833333333-0.6044861111111120.0899027777777768
4016.0715.441805555555615.9779166666667-0.5361111111111120.628194444444444
4115.8215.588097222222216.1216666666667-0.5335694444444440.231902777777773
4215.8715.885430555555616.2675-0.382069444444444-0.0154305555555574
4315.7216.308013888888916.44625-0.138236111111110-0.588013888888888
4417.0717.052013888888916.606250.4457638888888890.0179861111111101
4516.8317.095638888888916.74291666666670.352722222222221-0.265638888888891
4617.5217.291305555555616.84541666666670.445888888888890.228694444444447
4717.7617.521055555555616.93250.5885555555555560.238944444444446
4817.3617.230972222222217.04958333333330.1813888888888900.129027777777779
4917.9517.772930555555617.188750.5841805555555540.177069444444442
5016.7116.910972222222217.315-0.404027777777779-0.200972222222223
5117.1416.806763888888917.41125-0.6044861111111120.333236111111109
5216.7216.954722222222217.4908333333333-0.536111111111112-0.234722222222221
5317.2617.002263888888917.5358333333333-0.5335694444444440.257736111111114
5417.2417.182930555555617.565-0.3820694444444440.0570694444444477
5517.6917.435930555555617.5741666666667-0.1382361111111100.254069444444450
5618.1318.022013888888917.576250.4457638888888890.107986111111117
5718.0817.911472222222217.558750.3527222222222210.168527777777776
5818.1817.980055555555617.53416666666670.445888888888890.199944444444444
5918.1818.110222222222217.52166666666670.5885555555555560.0697777777777802
6017.6417.679305555555617.49791666666670.181388888888890-0.0393055555555542
6117.8918.047097222222217.46291666666670.584180555555554-0.157097222222223
6216.8217.034722222222217.43875-0.404027777777779-0.214722222222221
6316.6116.810513888888917.415-0.604486111111112-0.200513888888892
6416.6616.828888888888917.365-0.536111111111112-0.168888888888890
6517.0216.775597222222217.3091666666667-0.5335694444444440.244402777777776
6616.9116.892097222222217.2741666666667-0.3820694444444440.0179027777777740
6717.1817.123430555555617.2616666666667-0.1382361111111100.0565694444444418
6818.0617.702013888888917.256250.4457638888888890.357986111111114
6917.5817.590222222222217.23750.352722222222221-0.0102222222222217
7017.4817.664222222222217.21833333333330.44588888888889-0.184222222222225
7117.5417.778972222222217.19041666666670.588555555555556-0.238972222222223
7217.4417.330138888888917.148750.1813888888888900.109861111111112
7317.7917.720847222222217.13666666666670.5841805555555540.0691527777777807
7416.7916.733472222222217.1375-0.4040277777777790.0565277777777773
7516.1916.518430555555617.1229166666667-0.604486111111112-0.328430555555549
7616.6216.603055555555617.1391666666667-0.5361111111111120.016944444444448
7716.3916.645597222222217.1791666666667-0.533569444444444-0.255597222222224
7816.5416.810430555555617.1925-0.382069444444444-0.270430555555556
7917.2617.077597222222217.2158333333333-0.1382361111111100.182402777777778
801817.693680555555617.24791666666670.4457638888888890.306319444444448
8117.2917.646055555555617.29333333333330.352722222222221-0.356055555555557
8218.1617.788805555555617.34291666666670.445888888888890.371194444444441
8317.8217.976055555555617.38750.588555555555556-0.156055555555554
8417.4817.623055555555617.44166666666670.181388888888890-0.143055555555556
8518.3118.067930555555617.483750.5841805555555540.242069444444443
8617.0417.118472222222217.5225-0.404027777777779-0.0784722222222243
8717.0316.979680555555617.5841666666667-0.6044861111111120.0503194444444475
8816.9717.100972222222217.6370833333333-0.536111111111112-0.130972222222226
8917.1117.137680555555617.67125-0.533569444444444-0.0276805555555555
9017.1217.334180555555617.71625-0.382069444444444-0.214180555555554
9117.6917.608430555555617.7466666666667-0.1382361111111100.0815694444444439
9218.518.242847222222217.79708333333330.4457638888888890.257152777777780
9318.2718.224805555555617.87208333333330.3527222222222210.0451944444444443
9418.4518.387972222222217.94208333333330.445888888888890.0620277777777751
9518.3518.610638888888918.02208333333330.588555555555556-0.260638888888888
9618.0318.310555555555618.12916666666670.181388888888890-0.280555555555555
9718.4918.824597222222218.24041666666670.584180555555554-0.334597222222225
9818.0717.930138888888918.3341666666667-0.4040277777777790.139861111111109
9917.817.830930555555618.4354166666667-0.604486111111112-0.0309305555555568
10017.8817.988472222222218.5245833333333-0.536111111111112-0.108472222222225
10118.1218.098097222222218.6316666666667-0.5335694444444440.0219027777777754
10218.6818.395847222222218.7779166666667-0.3820694444444440.284152777777781
10318.818.789263888888918.9275-0.1382361111111100.0107361111111111
10419.6419.502013888888919.056250.4457638888888890.137986111111115
10519.5619.501888888888919.14916666666670.3527222222222210.0581111111111134
10619.319.675472222222219.22958333333330.44588888888889-0.375472222222221
10720.0719.890638888888919.30208333333330.5885555555555560.179361111111113
10819.8219.524305555555619.34291666666670.1813888888888900.295694444444447
10920.2919.957930555555619.373750.5841805555555540.332069444444443
11019.3619.008472222222219.4125-0.4040277777777790.351527777777775
11118.7418.873847222222219.4783333333333-0.604486111111112-0.133847222222226
11218.8719.037222222222219.5733333333333-0.536111111111112-0.167222222222222
11318.8719.107680555555619.64125-0.533569444444444-0.237680555555556
11418.9119.312097222222219.6941666666667-0.382069444444444-0.402097222222221
11519.3119.624680555555619.7629166666667-0.138236111111110-0.314680555555558
11620.0620.267013888888919.821250.445763888888889-0.207013888888888
11720.7220.240638888888919.88791666666670.3527222222222210.479361111111107
11820.4220.404638888888919.958750.445888888888890.0153611111111154
11920.5820.598555555555520.010.588555555555556-0.018555555555551
12020.5820.237638888888920.056250.1813888888888900.34236111111111
12121.1820.685013888888920.10083333333330.5841805555555540.494986111111110
12219.8719.736805555555620.1408333333333-0.4040277777777790.133194444444445
12319.8319.525097222222220.1295833333333-0.6044861111111120.304902777777777
12419.4819.538472222222220.0745833333333-0.536111111111112-0.0584722222222211
12519.4919.469763888888920.0033333333333-0.5335694444444440.0202361111111102
12619.419.515013888888919.8970833333333-0.382069444444444-0.115013888888893
12719.89NANA-0.138236111111110NA
12820.44NANA0.445763888888889NA
12920.07NANA0.352722222222221NA
13019.75NANA0.44588888888889NA
13119.54NANA0.588555555555556NA
13219.07NANA0.181388888888890NA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/1843f1250588912.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/1843f1250588912.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/26axj1250588912.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/26axj1250588912.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/3w9qs1250588912.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/3w9qs1250588912.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/4gc3d1250588912.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250589122irmufisq66eytru/4gc3d1250588912.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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