Opgave 9 Oefening 2 Anke Winckelmans

*Unverified author*

R Software Module: rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Tue, 02 Jun 2009 13:29:18 -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/02/t1243971150295x3f287c1xs0s.htm/, Retrieved Tue, 02 Jun 2009 21:32:34 +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/02/t1243971150295x3f287c1xs0s.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 «

3779.7 3795.5 3813.1 3826.9 3833.3 3844.8 3851.3 3851.8 3854.1 3858.4 3861.6 3856.3 3855.8 3860.4 3855.1 3839.5 3833 3833.6 3826.8 3818.2 3811.4 3806.8 3810.3 3818.2 3858.9 3867.8 3872.3 3873.3 3876.7 3882.6 3883.5 3882.2 3888.1 3893.7 3901.9 3914.3 3930.3 3948.3 3971.5 3990.1 3993 3998 4015.8 4041.2 4060.7 4076.7 4103 4125.3 4139.7 4146.7 4158 4155.1 4144.8 4148.2 4142.5 4142.1 4145.4 4146.3 4143.5 4149.2 4158.9 4166.1 4179.1 4194.4 4211.7 4226.3 4235.8 4243.6 4258.7 4278.2 4298 4315.1 4334.3 4356 4374 4395.5

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 3779.7 NA NA 0.999963339519623 NA 2 3795.5 NA NA 1.00009011360544 NA 3 3813.1 3811.10302055211 3810.5 1.00015825234277 1.00052398988879 4 3826.9 3822.55307325326 3823.3625 0.999788294532172 1.00113717891248 5 3833.3 3834.15943272009 3834.3 0.999963339519623 0.99977584846557 6 3844.8 3842.5337333684 3842.1875 1.00009011360544 1.00058978444663 7 3851.3 3848.50893918973 3847.9 1.00015825234277 1.00072523173374 8 3851.8 3851.38446819683 3852.2 0.999788294532172 1.00010789154046 9 3854.1 3855.04616697431 3855.1875 0.999963339519623 0.999754564035468 10 3858.4 3857.38507155544 3857.0375 1.00009011360544 1.00026311307420 11 3861.6 3858.42300786607 3857.8125 1.00015825234277 1.00082339135119 12 3856.3 3857.45818208612 3858.275 0.999788294532172 0.99969975511556 13 3855.8 3857.57107440659 3857.7125 0.999963339519623 0.999540883532038 14 3860.4 3855.14736992625 3854.8 1.00009011360544 1.00136249786836 15 3855.1 3850.45924778180 3849.85 1.00015825234277 1.00120524641856 16 3839.5 3842.83627827858 3843.65 0.999788294532172 0.999131818782538 17 3833 3836.62184244366 3836.7625 0.999963339519623 0.99905598138352 18 3833.6 3830.90768579774 3830.5625 1.00009011360544 1.00070278754360 19 3826.8 3825.80534686155 3825.2 1.00015825234277 1.00025998529676 20 3818.2 3818.34146506254 3819.15 0.999788294532172 0.999962951175572 21 3811.4 3813.59768655122 3813.7375 0.999963339519623 0.99942372354615 22 3806.8 3812.01848377701 3811.675 1.00009011360544 0.998631044471788 23 3810.3 3818.21664612190 3817.6125 1.00015825234277 0.997926611594987 24 3818.2 3830.36391930429 3831.175 0.999788294532172 0.996824343701916 25 3858.9 3846.40898362921 3846.55 0.999963339519623 1.00324744883447 26 3867.8 3861.5354455269 3861.1875 1.00009011360544 1.00162229625015 27 3872.3 3870.91248404221 3870.3 1.00015825234277 1.00035844673924 28 3873.3 3873.55477362808 3874.375 0.999788294532172 0.999934227436303 29 3876.7 3877.48284440478 3877.625 0.999963339519623 0.999798104998476 30 3882.6 3880.48715317973 3880.1375 1.00009011360544 1.00054447978743 31 3883.5 3883.28944241495 3882.675 1.00015825234277 1.00005422145018 32 3882.2 3884.66492105107 3885.4875 0.999788294532172 0.999365473959487 33 3888.1 3889.03242097623 3889.175 0.999963339519623 0.999760243455107 34 3893.7 3895.83853642357 3895.4875 1.00009011360544 0.999451071597661 35 3901.9 3905.39293979172 3904.775 1.00015825234277 0.999105611177781 36 3914.3 3916.0457761457 3916.875 0.999788294532172 0.999554199249576 37 3930.3 3932.25583632697 3932.4 0.999963339519623 0.999502617223198 38 3948.3 3950.93100055681 3950.575 1.00009011360544 0.999334080864374 39 3971.5 3968.51542749270 3967.8875 1.00015825234277 1.00075206272013 40 3990.1 3981.0945020587 3981.9375 0.999788294532172 1.00226206585567 41 3993 3993.54108949778 3993.6875 0.999963339519623 0.999864508844244 42 3998 4005.97346018437 4005.6125 1.00009011360544 0.99800960733674 43 4015.8 4021.09874760963 4020.4625 1.00015825234277 0.998682263743765 44 4041.2 4037.90747189549 4038.7625 0.999788294532172 1.00081540454491 45 4060.7 4059.35117677991 4059.5 0.999963339519623 1.00033227556852 46 4076.7 4081.28024573886 4080.9125 1.00009011360544 0.998877742898533 47 4103 4101.94904033338 4101.3 1.00015825234277 1.00025620983008 48 4125.3 4119.05278935046 4119.925 0.999788294532172 1.00151666195337 49 4139.7 4135.39838875038 4135.55 0.999963339519623 1.00104019270823 50 4146.7 4146.52362452519 4146.15 1.00009011360544 1.00004253574579 51 4158 4151.1693283268 4150.5125 1.00015825234277 1.00164548134103 52 4155.1 4150.45863915245 4151.3375 0.999788294532172 1.00111827661738 53 4144.8 4149.43537412888 4149.5875 0.999963339519623 0.998882890390875 54 4148.2 4146.39861326099 4146.025 1.00009011360544 1.00043444610782 55 4142.5 4145.13087287828 4144.475 1.00015825234277 0.999365310056795 56 4142.1 4143.43512638336 4144.3125 0.999788294532172 0.999677773069292 57 4145.4 4144.04807163722 4144.2 0.999963339519623 1.00032623375487 58 4146.3 4145.58604004369 4145.2125 1.00009011360544 1.00017222171954 59 4143.5 4148.44389708917 4147.7875 1.00015825234277 0.998808252633563 60 4149.2 4151.07100948285 4151.95 0.999788294532172 0.999549270663263 61 4158.9 4158.72253364467 4158.875 0.999963339519623 1.00004267328582 62 4166.1 4169.35068136824 4168.975 1.00009011360544 0.999220338700997 63 4179.1 4181.88668865188 4181.225 1.00015825234277 0.99933362884761 64 4194.4 4194.46182146555 4195.35 0.999788294532172 0.999985261168612 65 4211.7 4209.80816075238 4209.9625 0.999963339519623 1.00044938846983 66 4226.3 4223.58056777849 4223.2 1.00009011360544 1.00064386891119 67 4235.8 4235.89523427839 4235.225 1.00015825234277 0.999977517319688 68 4243.6 4246.68826250117 4247.5875 0.999788294532172 0.999272783328967 69 4258.7 4261.69375853171 4261.85 0.999963339519623 0.99929751908482 70 4278.2 4278.94805669297 4278.5625 1.00009011360544 0.999825177430747 71 4298 4297.63000240425 4296.95 1.00015825234277 1.00008609340393 72 4315.1 4315.21125273767 4316.125 0.999788294532172 0.99997421847248 73 4334.3 4335.1910639864 4335.35 0.999963339519623 0.999794457966616 74 4356 4355.29243574033 4354.9 1.00009011360544 1.00016246079227 75 4374 NA NA 1.00015825234277 NA 76 4395.5 NA NA 0.999788294532172 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/1wsua1243970956.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/1wsua1243970956.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/26c6s1243970956.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/26c6s1243970956.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/37zn91243970956.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/37zn91243970956.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/4kovo1243970956.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243971150295x3f287c1xs0s/4kovo1243970956.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 4 ;

Parameters (R input):

par1 = multiplicative ; 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')

Copyright

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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