Home » date » 2010 » Dec » 18 »

*The author of this computation has been verified*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Sat, 18 Dec 2010 15:28:05 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw.htm/, Retrieved Sat, 18 Dec 2010 16:26:39 +0100
 
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/2010/Dec/18/t1292685998xrojnciuy9l6smw.htm/},
    year = {2010},
}
@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 = {2010},
    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 «
13.193 15.234 14.718 16.961 13.945 15.876 16.226 18.316 16.748 17.904 17.209 18.950 17.225 18.710 17.236 18.687 17.580 19.568 17.381 19.580 17.260 18.661 15.658 18.674 15.908 17.475 17.725 19.562 16.368 19.555 17.743 19.867 15.703 19.324 18.162 19.074 15.323 19.704 18.375 18.352 13.927 17.795 16.761 18.902 16.239 19.158 18.279 15.698 16.239 18.431 18.414 19.801 14.995 18.706 18.232 19.409 16.263 19.017 20.298 19.891 15.203 17.845 17.502 18.532 15.737 17.770 17.224 17.601 14.940 18.507 17.635 19.392 15.699 17.661 18.243 19.643 15.770 17.344 17.229 17.322 16.152 17.919 16.918 18.114 16.308 17.759 16.021 17.952 15.954 17.762 16.610 17.751 15.458 18.106 15.990 15.349 13.185 15.409 16.007 16.633 14.800 15.974 15.693
 
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'RServer@AstonUniversity' @ vre.aston.ac.uk


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
113.193NANA-1.6781015625NA
215.234NANA0.726768229166667NA
314.71815.057523437515.1205-0.0629765625000006-0.339523437499999
416.96116.309059895833315.294751.014309895833330.651940104166668
513.94513.885398437515.5635-1.67810156250.0596015624999993
615.87616.648143229166715.9213750.726768229166667-0.772143229166668
716.22616.378148437516.441125-0.0629765625000006-0.152148437499999
818.31618.059309895833317.0451.014309895833330.256690104166665
916.74815.743273437517.421375-1.67810156251.0047265625
1017.90418.350268229166717.62350.726768229166667-0.446268229166666
1117.20917.699398437517.762375-0.0629765625000006-0.490398437499998
1218.9518.937059895833317.922751.014309895833330.0129401041666668
1317.22516.348773437518.026875-1.67810156250.876226562500001
1418.7118.724143229166717.9973750.726768229166667-0.0141432291666668
1517.23617.945898437518.008875-0.0629765625000006-0.709898437499998
1618.68719.174809895833318.16051.01430989583333-0.487809895833333
1717.5816.607773437518.285875-1.67810156250.972226562500001
1819.56819.142393229166718.4156250.7267682291666670.425606770833333
1917.38118.424273437518.48725-0.0629765625000006-1.0432734375
2019.5819.348184895833318.3338751.014309895833330.231815104166664
2117.2616.327023437518.005125-1.67810156250.932976562500002
2218.66118.403268229166717.67650.7267682291666670.257731770833338
2315.65817.331273437517.39425-0.0629765625000006-1.6732734375
2418.67418.091309895833317.0771.014309895833330.58269010416667
2515.90815.509023437517.187125-1.67810156250.3989765625
2617.47518.283268229166717.55650.726768229166667-0.808268229166664
2717.72517.662023437517.725-0.06297656250000060.0629765625000012
2819.56219.056809895833318.04251.014309895833330.505190104166669
2916.36816.626648437518.30475-1.6781015625-0.2586484375
3019.55519.071893229166718.3451250.7267682291666670.483106770833334
3117.74318.237148437518.300125-0.0629765625000006-0.494148437500002
3219.86719.202434895833318.1881251.014309895833330.66456510416667
3315.70316.533523437518.211625-1.6781015625-0.830523437500002
3419.32418.891643229166718.1648750.7267682291666670.432356770833337
3518.16217.955273437518.01825-0.06297656250000060.206726562499998
3619.07419.032559895833318.018251.014309895833330.0414401041666679
3715.32316.414273437518.092375-1.6781015625-1.0912734375
3819.70418.755518229166718.028750.7267682291666670.948481770833332
3918.37517.701023437517.764-0.06297656250000060.673976562500002
4018.35218.365184895833317.3508751.01430989583333-0.0131848958333336
4113.92715.232398437516.9105-1.6781015625-1.3053984375
4217.79517.504268229166716.77750.7267682291666670.290731770833336
4316.76117.072273437517.13525-0.0629765625000006-0.311273437499999
4418.90218.608934895833317.5946251.014309895833330.293065104166669
4516.23916.276648437517.95475-1.6781015625-0.0376484374999997
4619.15818.470768229166717.7440.7267682291666670.687231770833336
4718.27917.280523437517.3435-0.06297656250000060.998476562499999
4815.69818.266934895833317.2526251.01430989583333-2.56893489583333
4916.23915.500523437517.178625-1.67810156250.7384765625
5018.43118.435143229166717.7083750.726768229166667-0.00414322916666876
5118.41418.002773437518.06575-0.06297656250000060.411226562500001
5219.80118.958934895833317.9446251.014309895833330.842065104166664
5314.99516.278148437517.95625-1.6781015625-1.2831484375
5418.70618.611268229166717.88450.7267682291666670.0947317708333344
5518.23217.931023437517.994-0.06297656250000060.300976562500001
5619.40919.205684895833318.1913751.014309895833330.203315104166666
5716.26316.810398437518.4885-1.6781015625-0.547398437499997
5819.01719.533768229166718.8070.726768229166667-0.516768229166665
5920.29818.671773437518.73475-0.06297656250000061.6262265625
6019.89119.470059895833318.455751.014309895833330.420940104166668
6115.20316.281648437517.95975-1.6781015625-1.0786484375
6217.84518.167143229166717.4403750.726768229166667-0.322143229166667
6317.50217.274273437517.33725-0.06297656250000060.227726562499999
6418.53218.408934895833317.3946251.014309895833330.12306510416667
6515.73715.672398437517.3505-1.67810156250.0646015624999983
6617.7717.926143229166717.1993750.726768229166667-0.156143229166666
6717.22416.920398437516.983375-0.06297656250000060.303601562500003
6817.60117.990184895833316.9758751.01430989583333-0.389184895833335
6914.9415.441273437517.119375-1.6781015625-0.5012734375
7018.50718.121393229166717.3946250.7267682291666670.385606770833334
7117.63517.650398437517.713375-0.0629765625000006-0.0153984374999965
7219.39218.716809895833317.70251.014309895833330.675190104166667
7315.69915.994648437517.67275-1.6781015625-0.295648437499999
7417.66118.506893229166717.7801250.726768229166667-0.845893229166663
7518.24317.757398437517.820375-0.06297656250000060.485601562499998
7619.64318.803934895833317.7896251.014309895833330.839065104166668
7715.7715.945148437517.62325-1.6781015625-0.175148437499999
7817.34417.933143229166717.2063750.726768229166667-0.589143229166666
7917.22916.901023437516.964-0.06297656250000060.327976562500002
8017.32218.097934895833317.0836251.01430989583333-0.77593489583333
8116.15215.438523437517.116625-1.67810156250.713476562500002
8217.91917.903518229166717.176750.7267682291666670.0154817708333326
8316.91817.232273437517.29525-0.0629765625000006-0.314273437500002
8418.11418.309059895833317.294751.01430989583333-0.195059895833332
8516.30815.484523437517.162625-1.67810156250.823476562499998
8617.75917.757018229166717.030250.7267682291666670.00198177083333562
8716.02116.902773437516.96575-0.0629765625000006-0.881773437499998
8817.95217.936184895833316.9218751.014309895833330.0158151041666699
8915.95415.317773437516.995875-1.67810156250.636226562500003
9017.76217.771143229166717.0443750.726768229166667-0.00914322916666777
9116.6116.894273437516.95725-0.0629765625000006-0.284273437500001
9217.75117.952559895833316.938251.01430989583333-0.201559895833331
9315.45815.225648437516.90375-1.67810156250.232351562499996
9418.10617.252768229166716.5260.7267682291666670.853231770833336
9515.9915.878648437515.941625-0.06297656250000060.111351562499999
9615.34916.334684895833315.3203751.01430989583333-0.985684895833334
9713.18513.307273437514.985375-1.6781015625-0.122273437500001
9815.40915.874768229166715.1480.726768229166667-0.465768229166668
9916.00715.447398437515.510375-0.06297656250000060.559601562500001
10016.63316.797184895833315.7828751.01430989583333-0.164184895833335
10114.8NA15.81425NANA
10215.974NANANANA
10315.693NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/1sr441292686081.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/1sr441292686081.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/2li3p1292686081.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/2li3p1292686081.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/3li3p1292686081.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/3li3p1292686081.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/4ju9h1292686081.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292685998xrojnciuy9l6smw/4ju9h1292686081.ps (open in new window)


 
Parameters (Session):
par1 = additive ; par2 = 4 ;
 
Parameters (R input):
par1 = additive ; par2 = 4 ;
 
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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