Multiplicatief decompositiemodel Eigen reeks

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 29 May 2011 13:40:24 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8.htm/, Retrieved Sun, 29 May 2011 15:36:47 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 577 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516 528 533 536 537 524 536 587 597 581 564 558 575 580 575 563 552 537 545 601 604 586 564 549 551 556

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 476 NA NA 1.00255543259767 NA 2 475 NA NA 0.99441556935843 NA 3 470 NA NA 0.977453795257913 NA 4 461 NA NA 0.965910970979626 NA 5 455 NA NA 0.94534609794411 NA 6 456 NA NA 0.951674576117548 NA 7 517 516.229187835907 493.291666666667 1.04649890261524 1.00149315881832 8 525 526.083076142731 496.833333333333 1.05887234379617 0.997941245039335 9 523 522.442574468536 500.25 1.04436296745335 1.00106696038704 10 519 513.04492166495 503.916666666667 1.01811461220099 1.01160732342058 11 509 504.285805888034 507.833333333333 0.993014386389303 1.0093482585806 12 512 512.786314245142 511.875 1.00178034528965 0.998466584962785 13 519 517.485695792498 516.166666666667 1.00255543259767 1.00292627259036 14 517 517.717605797232 520.625 0.99441556935843 0.998613904976 15 510 513.36687871775 525.208333333333 0.977453795257913 0.993441573936052 16 509 511.369366552797 529.416666666667 0.965910970979626 0.995366623994767 17 501 503.790691362715 532.916666666667 0.94534609794411 0.994460613483813 18 507 510.375144550373 536.291666666667 0.951674576117548 0.993386933932007 19 569 564.9785950494 539.875 1.04649890261524 1.00711780054295 20 580 575.497118853219 543.5 1.05887234379617 1.00782433308398 21 578 571.4841188152 547.208333333333 1.04436296745335 1.01140168373936 22 565 560.514515458822 550.541666666667 1.01811461220099 1.00800244135963 23 547 549.633462866479 553.5 0.993014386389303 0.995208692620815 24 555 557.490762153692 556.5 1.00178034528965 0.995532191163007 25 562 560.470259965123 559.041666666667 1.00255543259767 1.00272938663146 26 561 558.240040248588 561.375 0.99441556935843 1.00494403760465 27 555 551.40612224987 564.125 0.977453795257913 1.00651766022377 28 544 548.154476030937 567.5 0.965910970979626 0.992420975815031 29 537 540.147126712816 571.375 0.94534609794411 0.994173575018406 30 543 547.21288126759 575 0.951674576117548 0.992301202307535 31 594 604.745553348779 577.875 1.04649890261524 0.982231281752671 32 611 614.410677487728 580.25 1.05887234379617 0.994448863581483 33 613 608.471973912506 582.625 1.04436296745335 1.00744163458898 34 611 595.639469579756 585.041666666667 1.01811461220099 1.02578830182473 35 594 583.395952003716 587.5 0.993014386389303 1.01817641682268 36 595 590.883440330014 589.833333333333 1.00178034528965 1.00696678801438 37 591 593.554589240846 592.041666666667 1.00255543259767 0.995696117447069 38 589 590.599980234794 593.916666666667 0.99441556935843 0.997290923995362 39 584 581.870098868742 595.291666666667 0.977453795257913 1.00366044093931 40 573 575.642692413399 595.958333333333 0.965910970979626 0.995409144512337 41 567 563.465663795437 596.041666666667 0.94534609794411 1.006272496146 42 569 567.356659795411 596.166666666667 0.951674576117548 1.0028964852641 43 621 624.062178926219 596.333333333333 1.04649890261524 0.995093150923698 44 629 631.573233393424 596.458333333333 1.05887234379617 0.995925676932826 45 628 622.788449591346 596.333333333333 1.04436296745335 1.0083680909819 46 612 607.008416082667 596.208333333333 1.01811461220099 1.00822325322859 47 595 592.333081481219 596.5 0.993014386389303 1.00450239671252 48 597 597.979384442482 596.916666666667 1.00178034528965 0.998362176911173 49 593 598.567366403834 597.041666666667 1.00255543259767 0.99069884742083 50 590 593.541792960812 596.875 0.99441556935843 0.994032782522112 51 580 582.969734388407 596.416666666667 0.977453795257913 0.99490585151642 52 574 574.797520313792 595.083333333333 0.965910970979626 0.99861251956453 53 573 560.472067818614 592.875 0.94534609794411 1.02235246482513 54 573 562.281062056118 590.833333333333 0.951674576117548 1.01906330955676 55 620 616.039020672835 588.666666666667 1.04649890261524 1.00642975395104 56 626 620.102116335633 585.625 1.05887234379617 1.00951114906561 57 620 607.73221681056 581.916666666667 1.04436296745335 1.02018616563365 58 588 588.385402967824 577.916666666667 1.01811461220099 0.99934498210547 59 566 569.328248196534 573.333333333333 0.993014386389303 0.994154078588096 60 577 568.67730934276 567.666666666667 1.00178034528965 1.01463517274297 61 561 563.310833690816 561.875 1.00255543259767 0.995897764515418 62 549 553.516566294136 556.625 0.99441556935843 0.991840232850889 63 532 538.414132221234 550.833333333333 0.977453795257913 0.98808699133737 64 526 526.461725474353 545.041666666667 0.965910970979626 0.999122964781652 65 511 510.64445057281 540.166666666667 0.94534609794411 1.00069627590546 66 499 509.344163759579 535.208333333333 0.951674576117548 0.97969120980355 67 555 555.429292563036 530.75 1.04649890261524 0.999227097726417 68 565 558.24632358554 527.208333333333 1.05887234379617 1.01209802219759 69 542 547.115649574622 523.875 1.04436296745335 0.990649783864528 70 527 530.183184303667 520.75 1.01811461220099 0.9939960670238 71 510 513.884944956464 517.5 0.993014386389303 0.992440049091546 72 514 515.79165528101 514.875 1.00178034528965 0.996526397310491 73 517 514.18561749353 512.875 1.00255543259767 1.00547347574634 74 508 507.607714175422 510.458333333333 0.99441556935843 1.0007728129688 75 493 496.709436956896 508.166666666667 0.977453795257913 0.99253197809242 76 490 489.032675348893 506.291666666667 0.965910970979626 1.00197803684676 77 469 477.478558303271 505.083333333333 0.94534609794411 0.982243059597483 78 478 480.437048510009 504.833333333333 0.951674576117548 0.994927434265183 79 528 528.874382909175 505.375 1.04649890261524 0.998346709658417 80 534 536.715919261684 506.875 1.05887234379617 0.994939745283836 81 518 532.320507535699 509.708333333333 1.04436296745335 0.973097960095518 82 506 522.759431923035 513.458333333333 1.01811461220099 0.967940450425957 83 502 514.091822953629 517.708333333333 0.993014386389303 0.976479254456612 84 516 523.346748718403 522.416666666667 1.00178034528965 0.985961986510102 85 528 528.639124980147 527.291666666667 1.00255543259767 0.998790999474035 86 533 529.401988737194 532.375 0.99441556935843 1.00679636899625 87 536 525.503596675536 537.625 0.977453795257913 1.01997398950429 88 537 524.167686918277 542.666666666667 0.965910970979626 1.02448131275922 89 524 517.498209782905 547.416666666667 0.94534609794411 1.01256388929311 90 536 525.522631553578 552.208333333333 0.951674576117548 1.01993704517624 91 587 582.725472272917 556.833333333333 1.04649890261524 1.00733540565922 92 597 593.762666783703 560.75 1.05887234379617 1.00545223436467 93 581 588.629077530892 563.625 1.04436296745335 0.987039244539373 94 564 575.616548873136 565.375 1.01811461220099 0.979818945622954 95 558 562.584025488973 566.541666666667 0.993014386389303 0.991851838514275 96 575 568.468605104158 567.458333333333 1.00178034528965 1.01148945577152 97 580 569.869217145726 568.416666666667 1.00255543259767 1.01777738215974 98 575 566.112496839342 569.291666666667 0.99441556935843 1.01569918207119 99 563 556.945027089665 569.791666666667 0.977453795257913 1.01087176043563 100 552 550.569253458387 570 0.965910970979626 1.00259866771097 101 537 538.492771041414 569.625 0.94534609794411 0.99722787171585 102 545 540.789077878797 568.25 0.951674576117548 1.00778662567987 103 601 592.580003605877 566.25 1.04649890261524 1.01420904577084 104 604 NA NA 1.05887234379617 NA 105 586 NA NA 1.04436296745335 NA 106 564 NA NA 1.01811461220099 NA 107 549 NA NA 0.993014386389303 NA 108 551 NA NA 1.00178034528965 NA 109 556 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/1mcyw1306676420.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/1mcyw1306676420.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/2j0ys1306676420.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/2j0ys1306676420.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/3dt551306676420.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/3dt551306676420.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/484kn1306676420.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/29/t13066762071sruzhn8irsc4a8/484kn1306676420.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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