voetbal prijzen

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 19 May 2008 08:38:53 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2.htm/, Retrieved Mon, 19 May 2008 16:39:50 +0200

User-defined keywords:

inkom multi

Dataseries X:

» Textbox « » Textfile « » CSV «

14,32 14,32 14,32 14,32 14,32 14,32 14,32 14,67 14,8 14,8 14,8 14,8 14,8 14,8 14,8 14,8 14,8 14,8 14,8 15,56 15,56 15,56 15,56 15,56 15,56 15,56 15,56 15,56 15,56 15,56 15,56 16,8 16,8 16,8 16,8 16,8 16,8 16,8 16,8 16,8 16,8 16,8 16,8 17,43 17,43 17,43 17,43 17,43 17,43 17,43 17,43 17,43 17,43 17,43 17,43 18,61 18,61 18,61 18,61 18,61 18,61 18,61 18,61 18,61 18,61 18,61 18,61 20 20 20 20 20 20 20 20 20 20 20 20 20,61 20,61 20,61 20,61 20,61 20,61 20,61 20,61 20,61 20,61 20,61 20,61 19,47 19,47 19,47 19,47 19,47

Text written by user:

tomas van gastel

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 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 14.32 NA NA 1.00250392959128 NA 2 14.32 NA NA 0.997820351868637 NA 3 14.32 NA NA 0.993066155881645 NA 4 14.32 NA NA 0.98842123559919 NA 5 14.32 NA NA 0.98382402218721 NA 6 14.32 NA NA 0.979273733192445 NA 7 14.32 14.1625900371554 14.5291666666667 0.974769603933839 1.01111448982366 8 14.67 14.9385220360295 14.5691666666667 1.02535185284193 0.982024859261053 9 14.8 14.9110136507470 14.6091666666667 1.02066147857489 0.992554922599684 10 14.8 14.8838173270669 14.6491666666667 1.01601802107516 0.994368559810628 11 14.8 14.8569277135423 14.6891666666667 1.01142073275377 0.996168271486548 12 14.8 14.8303395818230 14.7291666666667 1.00686888250000 0.997954222042215 13 14.8 14.8061476201219 14.7691666666667 1.00250392959128 0.999584792730719 14 14.8 14.7939339918924 14.82625 0.997820351868637 1.00041003347121 15 14.8 14.7917203918571 14.895 0.993066155881645 1.00055974612307 16 14.8 14.7851343158379 14.9583333333333 0.98842123559919 1.00100544802939 17 14.8 14.7786765199555 15.0216666666667 0.98382402218721 1.00144285450836 18 14.8 14.7723442652080 15.085 0.979273733192445 1.00187212904705 19 14.8 14.7661348835911 15.1483333333333 0.974769603933839 1.00229343133297 20 15.56 15.5973106014804 15.2116666666667 1.02535185284193 0.99760788238218 21 15.56 15.5906040852314 15.275 1.02066147857489 0.99803701735583 22 15.56 15.5840230799246 15.3383333333333 1.01601802107516 0.998458480213912 23 15.56 15.5775649856293 15.4016666666667 1.01142073275377 0.998872417759416 24 15.56 15.5712272678625 15.465 1.00686888250000 0.999278973476566 25 15.56 15.5672151866700 15.5283333333333 1.00250392959128 0.999536513976106 26 15.56 15.5776387265892 15.6116666666667 0.997820351868637 0.998867689327067 27 15.56 15.6060346396801 15.715 0.993066155881645 0.997050202646417 28 15.56 15.6351765784532 15.8183333333333 0.98842123559919 0.995191830544672 29 15.56 15.664118139924 15.9216666666667 0.98382402218721 0.993353080014211 30 15.56 15.6928615744089 16.025 0.979273733192445 0.991533629875026 31 15.56 15.7214090954463 16.1283333333333 0.974769603933839 0.98973316612612 32 16.8 16.6431694913792 16.2316666666667 1.02535185284193 1.00942311551307 33 16.8 16.6725052525208 16.335 1.02066147857489 1.00764700598669 34 16.8 16.7016429031072 16.4383333333333 1.01601802107516 1.00588906716922 35 16.8 16.7305846209686 16.5416666666667 1.01142073275377 1.00414901096429 36 16.8 16.7593325492125 16.645 1.00686888250000 1.00242655551276 37 16.8 16.7902699807713 16.7483333333333 1.00250392959128 1.00057950344097 38 16.8 16.7895746956297 16.82625 0.997820351868637 1.00062093915774 39 16.8 16.7617153785873 16.87875 0.993066155881645 1.00228405151549 40 16.8 16.7352070452388 16.93125 0.98842123559919 1.00387165540206 41 16.8 16.709021236822 16.98375 0.98382402218721 1.00544488883511 42 16.8 16.6831521370998 17.03625 0.979273733192445 1.00700394397533 43 16.8 16.6575940692244 17.08875 0.974769603933839 1.00854900954987 44 17.43 17.5758124475267 17.14125 1.02535185284193 0.991703800438132 45 17.43 17.548998297247 17.19375 1.02066147857489 0.993219083207407 46 17.43 17.5225007959675 17.24625 1.01601802107516 0.994721027720608 47 17.43 17.4963144007243 17.29875 1.01142073275377 0.996209807436842 48 17.43 17.4704336974782 17.35125 1.00686888250000 0.997685592803342 49 17.43 17.4473277646243 17.40375 1.00250392959128 0.99900685280531 50 17.43 17.4410682337039 17.4791666666667 0.997820351868637 0.999365392442964 51 17.43 17.4556203550096 17.5775 0.993066155881645 0.998532257548654 52 17.43 17.4711690235787 17.6758333333333 0.98842123559919 0.997643602238458 53 17.43 17.4866521410258 17.7741666666667 0.98382402218721 0.99676026373894 54 17.43 17.5020697964820 17.8725 0.979273733192445 0.99588221294281 55 17.43 17.5174220906944 17.9708333333333 0.974769603933839 0.995009420322138 56 18.61 18.5272535209762 18.0691666666667 1.02535185284193 1.00446620320330 57 18.61 18.5428674120093 18.1675 1.02066147857489 1.00362039950451 58 18.61 18.5584158366221 18.2658333333333 1.01601802107516 1.00277955639275 59 18.61 18.5738989064124 18.3641666666667 1.01142073275377 1.00194364649929 60 18.61 18.5893167431563 18.4625 1.00686888250000 1.00111264212286 61 18.61 18.6073083531555 18.5608333333333 1.00250392959128 1.00014465535764 62 18.61 18.6272271769877 18.6679166666667 0.997820351868637 0.999075161492151 63 18.61 18.6535064055419 18.78375 0.993066155881645 0.997667655367522 64 18.61 18.6807495106432 18.8995833333333 0.98842123559919 0.996212704923704 65 18.61 18.7078237085657 19.0154166666667 0.98382402218721 0.994770973359082 66 18.61 18.7347306081380 19.13125 0.979273733192445 0.993342279067317 67 18.61 18.7614717977149 19.2470833333333 0.974769603933839 0.99192644375942 68 20 19.8538024805905 19.3629166666667 1.02535185284193 1.00736370373144 69 20 19.8812097757906 19.47875 1.02066147857489 1.00597499978870 70 20 19.9084497821257 19.5945833333333 1.01601802107516 1.00459856085613 71 20 19.9355240678821 19.7104166666667 1.01142073275377 1.00323422308329 72 20 19.9624341816657 19.82625 1.00686888250000 1.00188182553252 73 20 19.9920169059035 19.9420833333333 1.00250392959128 1.00039931409292 74 20 19.9817683046494 20.0254166666667 0.997820351868637 1.00091241651252 75 20 19.9370444120189 20.07625 0.993066155881645 1.00315771920251 76 20 19.8940365773412 20.1270833333333 0.98842123559919 1.00532639126539 77 20 19.8515191343583 20.1779166666667 0.98382402218721 1.00747957194796 78 20 19.8094835303167 20.22875 0.979273733192445 1.00961743749612 79 20 19.7679214137766 20.2795833333333 0.974769603933839 1.01174016131315 80 20.61 20.8458303982150 20.3304166666667 1.02535185284193 0.988686927135547 81 20.61 20.8023567602044 20.38125 1.02066147857489 0.990753126560524 82 20.61 20.7593648747762 20.4320833333333 1.01601802107516 0.992804940051049 83 20.61 20.7168465839344 20.4829166666667 1.01142073275377 0.994842526660535 84 20.61 20.6747939160344 20.53375 1.00686888250000 0.996866042955612 85 20.61 20.6361256806659 20.5845833333333 1.00250392959128 0.998733983254891 86 20.61 20.5176809852988 20.5625 0.997820351868637 1.00449948582236 87 20.61 20.3255815455076 20.4675 0.993066155881645 1.01399312752039 88 20.61 20.1366116222445 20.3725 0.98842123559919 1.02350883985032 89 20.61 19.9494916099011 20.2775 0.98382402218721 1.03310903370445 90 20.61 19.7641921201565 20.1825 0.979273733192445 1.04279496347239 91 20.61 NA NA 0.974769603933839 NA 92 19.47 NA NA 1.02535185284193 NA 93 19.47 NA NA 1.02066147857489 NA 94 19.47 NA NA 1.01601802107516 NA 95 19.47 NA NA 1.01142073275377 NA 96 19.47 NA NA 1.00686888250000 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/10cyx1211207926.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/10cyx1211207926.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/2in8e1211207926.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/2in8e1211207926.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/39uzw1211207926.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/39uzw1211207926.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/4707x1211207926.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211207990jzyppkbid8ktcw2/4707x1211207926.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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