decomposite- uitvoer België naar EU -Tessa Buck

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 28 May 2009 14:16:52 -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/May/28/t12435418651bpm12um1culaim.htm/, Retrieved Thu, 28 May 2009 22:17:49 +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/May/28/t12435418651bpm12um1culaim.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 «

11025,1 10853,8 12252,6 11839,4 11669,1 11601,4 11178,4 9516,4 12102,8 12989 11610,2 10205,5 11356,2 11307,1 12648,6 11947,2 11714,1 12192,5 11268,8 9097,4 12639,8 13040,1 11687,3 11191,7 11391,9 11793,1 13933,2 12778,1 11810,3 13698,4 11956,6 10723,8 13938,9 13979,8 13807,4 12973,9 12509,8 12934,1 14908,3 13772,1 13012,6 14049,9 11816,5 11593,2 14466,2 13615,9 14733,9 13880,7 13527,5 13584 16170,2 13260,6 14741,9 15486,5 13154,5 12621,2 15031,6 15452,4 15428 13105,9 14716,8 14180 16202,2 14392,4 15140,6 15960,1 14351,3 13230,2 15202,1 17056 16077,7 13348,2 16707,5 16792,6 16831,3 17804,5 16370,2 17602,5 17065,6 14427,9 17818,5 18027,6

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 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 11025.1 NA NA 0.971461623531778 NA 2 10853.8 NA NA 0.973063902875244 NA 3 12252.6 NA NA 1.12097440246690 NA 4 11839.4 NA NA 1.00255718900844 NA 5 11669.1 NA NA 0.99716172053849 NA 6 11601.4 NA NA 1.06742905206057 NA 7 11178.4 10634.3328398421 11417.4375 0.931411522054935 1.05116138156966 8 9516.4 9659.12690693888 11450.1208333333 0.843582967161312 0.985223622350758 9 12102.8 12060.2662005415 11485.5083333333 1.05004200515358 1.00352677119652 10 12989 12293.2523556135 11506.5 1.06837460180016 1.05659589702222 11 11610.2 11972.5681650116 11512.8666666667 1.03992936873628 0.969733464030665 12 10205.5 10777.9067298330 11539.3708333333 0.934011644612313 0.946890732664385 13 11356.2 11237.6413866368 11567.7666666667 0.971461623531778 1.01055013318935 14 11307.1 11242.8533136133 11554.075 0.973063902875244 1.00571444673292 15 12648.6 12957.3337766615 11558.9916666667 1.12097440246690 0.976173047481607 16 11947.2 11613.1170215576 11583.4958333333 1.00255718900844 1.02876772685767 17 11714.1 11555.9451405410 11588.8375 0.99716172053849 1.01368601681088 18 12192.5 12417.5533817363 11633.1416666667 1.06742905206057 0.98187618971163 19 11268.8 10874.9009124635 11675.7208333333 0.931411522054935 1.03622093577745 20 9097.4 9867.77660907914 11697.4583333333 0.843582967161312 0.921930072031593 21 12639.8 12360.2894524640 11771.2333333333 1.05004200515358 1.02261359239288 22 13040.1 12670.2594947846 11859.3791666667 1.06837460180016 1.02918965514223 23 11687.3 12373.0882953024 11898.0083333333 1.03992936873628 0.944574201772833 24 11191.7 11175.2275000207 11964.7625 0.934011644612313 1.00147401920715 25 11391.9 11712.1032435697 12056.1666666667 0.971461623531778 0.972660483184734 26 11793.1 11825.2482772158 12152.5916666667 0.973063902875244 0.997281386702233 27 13933.2 13759.3862908999 12274.4875 1.12097440246690 1.01263237367026 28 12778.1 12399.3975609672 12367.7708333333 1.00255718900844 1.03054200312319 29 11810.3 12459.7974530801 12495.2625 0.99716172053849 0.947872551257282 30 13698.4 13511.3657218670 12657.8583333333 1.06742905206057 1.0138427366991 31 11956.6 11902.2245360021 12778.6958333333 0.931411522054935 1.00456851270395 32 10723.8 10859.2888793903 12872.8166666667 0.843582967161312 0.98752322726699 33 13938.9 13609.5813032705 12960.9875 1.05004200515358 1.02419756268698 34 13979.8 13934.8455437662 13043.0333333333 1.06837460180016 1.00322604625165 35 13807.4 13658.9999570961 13134.5458333333 1.03992936873628 1.01086463455378 36 12973.9 12328.2882255857 13199.2875 0.934011644612313 1.05236832256034 37 12509.8 12831.1582220133 13208.0958333333 0.971461623531778 0.974954854701893 38 12934.1 12881.8902604822 13238.4833333333 0.973063902875244 1.00405295639553 39 14908.3 14905.2369836482 13296.6791666667 1.12097440246690 1.00020549933927 40 13772.1 13337.5070320089 13303.4875 1.00255718900844 1.03258427282911 41 13012.6 13289.1036173279 13326.9291666667 0.99716172053849 0.979193207812197 42 14049.9 14307.0896039676 13403.3166666667 1.06742905206057 0.982023625273425 43 11816.5 12558.6911385091 13483.5041666667 0.931411522054935 0.940902190337872 44 11593.2 11433.0694091502 13552.9875 0.843582967161312 1.01400591434542 45 14466.2 14314.8507663820 13632.6458333333 1.05004200515358 1.01057288239242 46 13615.9 14598.1770762197 13663.9125 1.06837460180016 0.932712346816244 47 14733.9 14262.2716499781 13714.6541666667 1.03992936873628 1.03306824898561 48 13880.7 12932.8545045674 13846.5666666667 0.934011644612313 1.07328973623711 49 13527.5 13563.7171935348 13962.175 0.971461623531778 0.997329847488115 50 13584 13682.0163812189 14060.7583333333 0.973063902875244 0.992836115782357 51 16170.2 15836.1735298102 14127.15 1.12097440246690 1.02109262503098 52 13260.6 14263.6108807122 14227.2291666667 1.00255718900844 0.929680437225855 53 14741.9 14291.9907080785 14332.6708333333 0.99716172053849 1.03147981978936 54 15486.5 15295.5200109336 14329.3083333333 1.06742905206057 1.01248600825143 55 13154.5 13362.5691379066 14346.5791666667 0.931411522054935 0.984428957054645 56 12621.2 12165.2818500010 14420.9666666667 0.843582967161312 1.03747699030902 57 15031.6 15170.0968540545 14447.1333333333 1.05004200515358 0.990870404099135 58 15452.4 15486.7575872194 14495.625 1.06837460180016 0.997781486084098 59 15428 15140.74331814 14559.3958333333 1.03992936873628 1.01897242928066 60 13105.9 13632.5926784198 14595.7416666667 0.934011644612313 0.961365186296988 61 14716.8 14246.8166251482 14665.3416666667 0.971461623531778 1.03298865895572 62 14180 14343.5295489911 14740.5833333333 0.973063902875244 0.988599071906774 63 16202.2 16560.2249085436 14773.0625 1.12097440246690 0.978380431997703 64 14392.4 14884.9498759218 14846.9833333333 1.00255718900844 0.966909537483995 65 15140.6 14898.4644665100 14940.8708333333 0.99716172053849 1.01625238185011 66 15960.1 15987.9923703526 14978.0375 1.06742905206057 0.99825541758424 67 14351.3 14037.3767856354 15071.0791666667 0.931411522054935 1.02236338164591 68 13230.2 12875.5084097703 15262.8833333333 0.843582967161312 1.02754777356680 69 15202.1 16168.4986684296 15397.9541666667 1.05004200515358 0.940229535948405 70 17056 16630.6796280494 15566.3375 1.06837460180016 1.02557444322559 71 16077.7 16389.0182028635 15759.7416666667 1.03992936873628 0.98100446292694 72 13348.2 14831.5522928871 15879.4083333333 0.934011644612313 0.899986713218244 73 16707.5 NA 16060.9375 NA NA 74 16792.6 NA 16223.9375 NA NA 75 16831.3 NA 16382.8583333333 NA NA 76 17804.5 NA 16532.3583333333 NA NA 77 16370.2 NA NA NA NA 78 17602.5 NA NA NA NA 79 17065.6 NA NA NA NA 80 14427.9 NA NA NA NA 81 17818.5 NA NA NA NA 82 18027.6 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/1pnfw1243541810.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/1pnfw1243541810.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/28zbm1243541810.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/28zbm1243541810.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/31jnd1243541810.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/31jnd1243541810.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/49e381243541810.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/28/t12435418651bpm12um1culaim/49e381243541810.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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