Opgave 9 oef 2

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 14 Dec 2010 10:56:31 +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/14/t1292324103e3qmjin7dlv2cpr.htm/, Retrieved Tue, 14 Dec 2010 11:55:08 +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/14/t1292324103e3qmjin7dlv2cpr.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:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

771,28 766,78 757,59 747,73 746,59 744,5 744,29 743,79 738,89 736,74 732,77 731,58 731,48 730,08 724,19 716,81 714,84 713,18 713,16 713,15 713,6 707,08 704,11 704,36 704,36 701,93 696,44 686,58 684,48 683,74 683,7 683,52 678,77 674,71 670,28 668,85 668,85 669,35 672,28 671,6 671,96 671,18 671,18 681,14 682,23 679,98 679,69 679,69 679,7 681,21 672,32 669,98 667,91 666,04 666,04 666,27 664,45 660,76 660,4 660,69 660,69 662,23 661,41 659,02 655,43 652,59 652,59 648,2 645,84 644,67 642,71 640,14 640,14 639,64 630,28 614,57 614,7 615,08 615,08 614,43 604,55 598,98 594,05 593,05 593,05 593,34 584,72 580,7 577,08 569,92 569,92 568,86 559,38 548,22 545,61 545,33

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 4 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 771.28 NA NA 2.02737103174604 NA 2 766.78 NA NA 4.03653769841269 NA 3 757.59 NA NA 0.983442460317468 NA 4 747.73 NA NA -2.88018849206356 NA 5 746.59 NA NA -2.48114087301588 NA 6 744.5 NA NA -2.35417658730161 NA 7 744.29 744.621656746032 745.219166666667 -0.597509920634904 -0.33165674603174 8 743.79 744.164573412698 742.031666666667 2.13290674603177 -0.374573412698396 9 738.89 740.137966269841 739.110833333333 1.02713293650794 -1.24796626984119 10 736.74 735.851180555556 736.430833333333 -0.579652777777761 0.88881944444438 11 732.77 732.541716269841 733.819583333333 -1.27786706349205 0.228283730158751 12 731.58 731.154811507936 731.191666666667 -0.0368551587301448 0.425188492063626 13 731.48 730.61695436508 728.589583333333 2.02737103174604 0.863045634920809 14 730.08 730.052371031746 726.015833333333 4.03653769841269 0.0276289682541346 15 724.19 724.668859126984 723.685416666667 0.983442460317468 -0.478859126984162 16 716.81 718.51564484127 721.395833333333 -2.88018849206356 -1.70564484126999 17 714.84 716.484692460318 718.965833333333 -2.48114087301588 -1.64469246031751 18 713.18 714.283323412698 716.6375 -2.35417658730161 -1.1033234126985 19 713.16 713.775823412698 714.373333333333 -0.597509920634904 -0.615823412698433 20 713.15 714.203323412698 712.070416666667 2.13290674603177 -1.05332341269832 21 713.6 710.768382936508 709.74125 1.02713293650794 2.83161706349199 22 707.08 706.745763888889 707.325416666667 -0.579652777777761 0.334236111111181 23 704.11 703.522966269841 704.800833333333 -1.27786706349205 0.587033730158851 24 704.36 702.272311507936 702.309166666667 -0.0368551587301448 2.08768849206365 25 704.36 701.882371031746 699.855 2.02737103174604 2.47762896825395 26 701.93 701.429454365079 697.392916666667 4.03653769841269 0.500545634920741 27 696.44 695.690525793651 694.707083333333 0.983442460317468 0.749474206349191 28 686.58 689.02689484127 691.907083333334 -2.88018849206356 -2.44689484126991 29 684.48 686.667609126984 689.14875 -2.48114087301588 -2.18760912698417 30 683.74 683.905406746032 686.259583333333 -2.35417658730161 -0.165406746031749 31 683.7 682.702906746032 683.300416666667 -0.597509920634904 0.997093253968387 32 683.52 682.596240079365 680.463333333333 2.13290674603177 0.923759920635007 33 678.77 679.126299603175 678.099166666667 1.02713293650794 -0.356299603174648 34 674.71 675.888680555556 676.468333333333 -0.579652777777761 -1.17868055555550 35 670.28 674.044632936508 675.3225 -1.27786706349205 -3.76463293650806 36 668.85 674.24064484127 674.2775 -0.0368551587301448 -5.39064484126982 37 668.85 675.259871031746 673.2325 2.02737103174604 -6.40987103174598 38 669.35 676.64820436508 672.611666666667 4.03653769841269 -7.2982043650793 39 672.28 673.640109126984 672.656666666667 0.983442460317468 -1.36010912698430 40 671.6 670.140228174603 673.020416666667 -2.88018849206356 1.45977182539696 41 671.96 671.150942460317 673.632083333333 -2.48114087301588 0.809057539682726 42 671.18 672.121656746032 674.475833333333 -2.35417658730161 -0.941656746031754 43 671.18 674.782073412698 675.379583333333 -0.597509920634904 -3.60207341269847 44 681.14 678.458740079365 676.325833333333 2.13290674603177 2.68125992063494 45 682.23 677.848799603175 676.821666666667 1.02713293650794 4.38120039682531 46 679.98 676.176180555556 676.755833333333 -0.579652777777761 3.80381944444446 47 679.69 675.241716269841 676.519583333333 -1.27786706349205 4.44828373015889 48 679.69 676.099811507936 676.136666666667 -0.0368551587301448 3.5901884920637 49 679.7 677.735704365079 675.708333333333 2.02737103174604 1.96429563492075 50 681.21 678.911121031746 674.874583333333 4.03653769841269 2.29887896825414 51 672.32 674.497609126984 673.514166666667 0.983442460317468 -2.17760912698407 52 669.98 669.092311507937 671.9725 -2.88018849206356 0.88768849206349 53 667.91 667.886775793651 670.367916666667 -2.48114087301588 0.0232242063491412 54 666.04 666.418323412698 668.7725 -2.35417658730161 -0.378323412698478 55 666.04 666.591240079365 667.18875 -0.597509920634904 -0.55124007936513 56 666.27 667.738740079365 665.605833333333 2.13290674603177 -1.46874007936503 57 664.45 665.387549603175 664.360416666667 1.02713293650794 -0.937549603174716 58 660.76 662.869513888889 663.449166666667 -0.579652777777761 -2.10951388888907 59 660.4 661.194632936508 662.4725 -1.27786706349205 -0.794632936507924 60 660.69 661.355228174603 661.392083333333 -0.0368551587301448 -0.665228174603158 61 660.69 662.298621031746 660.27125 2.02737103174604 -1.60862103174611 62 662.23 662.99445436508 658.957916666667 4.03653769841269 -0.76445436507936 63 661.41 658.413025793651 657.429583333333 0.983442460317468 2.99697420634914 64 659.02 653.103561507936 655.98375 -2.88018849206356 5.91643849206355 65 655.43 652.095109126984 654.57625 -2.48114087301588 3.33489087301575 66 652.59 650.628740079365 652.982916666667 -2.35417658730161 1.96125992063503 67 652.59 650.672906746032 651.270416666667 -0.597509920634904 1.91709325396846 68 648.2 651.605823412698 649.472916666667 2.13290674603177 -3.40582341269828 69 645.84 648.261716269841 647.234583333333 1.02713293650794 -2.42171626984123 70 644.67 643.505763888889 644.085416666667 -0.579652777777761 1.16423611111111 71 642.71 639.258382936508 640.53625 -1.27786706349205 3.45161706349211 72 640.14 637.23939484127 637.27625 -0.0368551587301448 2.90060515873017 73 640.14 636.177787698413 634.150416666667 2.02737103174604 3.96221230158721 74 639.64 635.21695436508 631.180416666667 4.03653769841269 4.42304563492064 75 630.28 629.036359126984 628.052916666667 0.983442460317468 1.24364087301592 76 614.57 621.548561507936 624.42875 -2.88018849206356 -6.97856150793643 77 614.7 618.016359126984 620.4975 -2.48114087301588 -3.31635912698403 78 615.08 614.153740079365 616.507916666667 -2.35417658730161 0.926259920634948 79 615.08 611.986240079365 612.58375 -0.597509920634904 3.09375992063508 80 614.43 610.825406746032 608.6925 2.13290674603177 3.60459325396835 81 604.55 605.892132936508 604.865 1.02713293650794 -1.34213293650794 82 598.98 600.975763888889 601.555416666667 -0.579652777777761 -1.99576388888897 83 594.05 597.298799603175 598.576666666667 -1.27786706349205 -3.24879960317458 84 593.05 595.09064484127 595.1275 -0.0368551587301448 -2.04064484126991 85 593.05 593.391537698413 591.364166666667 2.02737103174604 -0.341537698412708 86 593.34 591.620287698413 587.58375 4.03653769841269 1.71971230158726 87 584.72 584.786359126984 583.802916666667 0.983442460317468 -0.066359126984139 88 580.7 576.92564484127 579.805833333333 -2.88018849206356 3.77435515873026 89 577.08 573.191359126984 575.6725 -2.48114087301588 3.88864087301602 90 569.92 569.311656746032 571.665833333333 -2.35417658730161 0.608343253968314 91 569.92 NA NA -0.597509920634904 NA 92 568.86 NA NA 2.13290674603177 NA 93 559.38 NA NA 1.02713293650794 NA 94 548.22 NA NA -0.579652777777761 NA 95 545.61 NA NA -1.27786706349205 NA 96 545.33 NA NA -0.0368551587301448 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/1w53w1292324186.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/1w53w1292324186.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/2w53w1292324186.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/2w53w1292324186.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/3w53w1292324186.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/3w53w1292324186.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/47wkz1292324186.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292324103e3qmjin7dlv2cpr/47wkz1292324186.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')

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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