iko 9.2 multi

*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 19:39:13 +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/t12923554499x70fzgps4bu8yb.htm/, Retrieved Tue, 14 Dec 2010 20:37:33 +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/t12923554499x70fzgps4bu8yb.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 «

101.02 101.15 101.51 101.75 101.8 101.8 101.8 101.82 101.99 102.25 102.34 102.35 102.35 102.39 102.49 102.67 102.68 102.7 102.71 102.72 102.83 102.92 103.04 103.08 103.09 103.11 103.18 103.18 103.22 103.25 103.25 103.25 103.47 103.57 103.66 103.7 103.7 103.75 103.85 104.02 104.13 104.17 104.18 104.2 104.5 104.78 104.88 104.89 104.9 104.95 105.24 105.35 105.44 105.46 105.47 105.48 105.75 106.1 106.19 106.23 106.24 106.25 106.35 106.48 106.52 106.55 106.55 106.56 106.89 107.09 107.24 107.28 107.3 107.31 107.47 107.35 107.31 107.32 107.32 107.34 107.53 107.72 107.75 107.79 107.81 107.9 107.8 107.86 107.8 107.74 107.75 107.83 107.8 107.81 107.86 107.83

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 9 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 101.02 NA NA 1.00024054631027 NA 2 101.15 NA NA 0.99992862511327 NA 3 101.51 NA NA 1.00024116109470 NA 4 101.75 NA NA 1.00032381797376 NA 5 101.8 NA NA 0.999958357905034 NA 6 101.8 NA NA 0.999459961038287 NA 7 101.8 101.742384830287 101.85375 0.998906616892231 1.00056628483605 8 101.82 101.783333684994 101.960833333333 0.998259138901315 1.00036023888861 9 101.99 102.020781426591 102.053333333333 0.999681030440858 0.99969828277964 10 102.25 102.232256147585 102.1325 1.00097673265204 1.00017356412823 11 102.34 102.330374898780 102.2075 1.00120221019768 1.00009405908294 12 102.35 102.365721891765 102.281666666667 1.00082180148054 0.999846414488415 13 102.35 102.381704952060 102.357083333333 1.00024054631027 0.999690326000387 14 102.39 102.425188891915 102.4325 0.99992862511327 0.999656442987357 15 102.49 102.529720218012 102.505 1.00024116109470 0.999612598006436 16 102.67 102.601130001615 102.567916666667 1.00032381797376 1.00067124015480 17 102.68 102.620726480004 102.625 0.999958357905034 1.00057759793785 18 102.7 102.629129657566 102.684583333333 0.999459961038287 1.00069054802151 19 102.71 102.633492774773 102.745833333333 0.998906616892231 1.00074544111438 20 102.72 102.627694539981 102.806666666667 0.998259138901315 1.00089942057485 21 102.83 102.832605730062 102.865416666667 0.999681030440858 0.999974660468408 22 102.92 103.015937514524 102.915416666667 1.00097673265204 0.999068711921297 23 103.04 103.082945226778 102.959166666667 1.00120221019768 0.999583391542764 24 103.08 103.089232652419 103.004583333333 1.00082180148054 0.999910440186801 25 103.09 103.074788297274 103.05 1.00024054631027 1.00014757927693 26 103.11 103.087224969126 103.094583333333 0.99992862511327 1.00022092971153 27 103.18 103.168207492511 103.143333333333 1.00024116109470 1.00011430369661 28 103.18 103.230500403757 103.197083333333 1.00032381797376 0.999510799583851 29 103.22 103.245700453695 103.25 0.999958357905034 0.999751074828474 30 103.25 103.245879741857 103.301666666667 0.999459961038287 1.0000399072404 31 103.25 103.239912333445 103.352916666667 0.998906616892231 1.00009771091749 32 103.25 103.224986258090 103.405 0.998259138901315 1.00024232255015 33 103.47 103.426582875649 103.459583333333 0.999681030440858 1.00041978689757 34 103.57 103.623613805971 103.5225 1.00097673265204 0.999482610150312 35 103.66 103.719960133017 103.595416666667 1.00120221019768 0.999421903624532 36 103.7 103.756864195823 103.671666666667 1.00082180148054 0.999451947625209 37 103.7 103.773706379008 103.74875 1.00024054631027 0.999289739360962 38 103.75 103.819672687021 103.827083333333 0.99992862511327 0.999328906697375 39 103.85 103.934642282200 103.909583333333 1.00024116109470 0.999185620113361 40 104.02 104.036594680407 104.002916666667 1.00032381797376 0.99984049189174 41 104.13 104.099831551072 104.104166666667 0.999958357905034 1.00028980305231 42 104.17 104.148308798344 104.204583333333 0.999459961038287 1.00020827224087 43 104.18 104.190122252763 104.304166666667 0.998906616892231 0.999902848249483 44 104.2 104.222413514376 104.404166666667 0.998259138901315 0.99978494535273 45 104.5 104.478747160188 104.512083333333 0.999681030440858 1.00020341782793 46 104.78 104.727607727359 104.625416666667 1.00097673265204 1.00050027183642 47 104.88 104.861330652642 104.735416666667 1.00120221019768 1.00017803843649 48 104.89 104.929910748975 104.84375 1.00082180148054 0.999619643734655 49 104.9 104.976495635946 104.95125 1.00024054631027 0.99927130701513 50 104.95 105.050834806692 105.058333333333 0.99992862511327 0.999040133218577 51 105.24 105.189111405073 105.16375 1.00024116109470 1.00048378196419 52 105.35 105.304921921280 105.270833333333 1.00032381797376 1.00042807190678 53 105.44 105.376028405348 105.380416666667 0.999958357905034 1.00060707919647 54 105.46 105.433864173230 105.490833333333 0.999459961038287 1.00024788835139 55 105.47 105.487036010362 105.6025 0.998906616892231 0.999838501383619 56 105.48 105.528469221105 105.7125 0.998259138901315 0.999540700045562 57 105.75 105.779165567286 105.812916666667 0.999681030440858 0.999724278716611 58 106.1 106.009692092430 105.90625 1.00097673265204 1.00085188350034 59 106.19 106.125765610604 105.998333333333 1.00120221019768 1.00060526667606 60 106.23 106.175933891819 106.08875 1.00082180148054 1.00050921245709 61 106.24 106.204707673436 106.179166666667 1.00024054631027 1.00033230472864 62 106.25 106.261581716933 106.269166666667 0.99992862511327 0.999891007486 63 106.35 106.387316962634 106.361666666667 1.00024116109470 0.99964923485525 64 106.48 106.484887224898 106.450416666667 1.00032381797376 0.99995410405152 65 106.52 106.530980308729 106.535416666667 0.999958357905034 0.999896928492568 66 106.55 106.565336137455 106.622916666667 0.999459961038287 0.99985608699779 67 106.55 106.594157510751 106.710833333333 0.998906616892231 0.99958574173499 68 106.56 106.613244152045 106.799166666667 0.998259138901315 0.999500585950009 69 106.89 106.855905343823 106.89 0.999681030440858 1.00031907133318 70 107.09 107.077400607259 106.972916666667 1.00097673265204 1.00011766621779 71 107.24 107.170770417498 107.042083333333 1.00120221019768 1.00064597447823 72 107.28 107.195104092993 107.107083333333 1.00082180148054 1.00079197560117 73 107.3 107.197029648755 107.17125 1.00024054631027 1.00096057093730 74 107.31 107.228179387876 107.235833333333 0.99992862511327 1.00076305139741 75 107.47 107.320875379656 107.295 1.00024116109470 1.00138952109566 76 107.35 107.382677851530 107.347916666667 1.00032381797376 0.999695687869 77 107.31 107.390944496527 107.395416666667 0.999958357905034 0.999246263296162 78 107.32 107.379896005701 107.437916666667 0.999459961038287 0.999442204659072 79 107.32 107.362899394667 107.480416666667 0.998906616892231 0.999600426265412 80 107.34 107.339061734287 107.52625 0.998259138901315 1.00000874113950 81 107.53 107.530273505608 107.564583333333 0.999681030440858 0.999997456478075 82 107.72 107.704679359721 107.599583333333 1.00097673265204 1.00014224674703 83 107.75 107.770657408441 107.64125 1.00120221019768 0.99980832066039 84 107.79 107.767657565257 107.679166666667 1.00082180148054 1.00020732040807 85 107.81 107.740493678917 107.714583333333 1.00024054631027 1.00064512718208 86 107.9 107.745225814445 107.752916666667 0.99992862511327 1.00143648300317 87 107.8 107.810576781442 107.784583333333 1.00024116109470 0.999901894769907 88 107.86 107.834490775981 107.799583333333 1.00032381797376 1.00023655904373 89 107.8 107.803427319163 107.807916666667 0.999958357905034 0.999968207697584 90 107.74 107.755942816042 107.814166666667 0.999459961038287 0.9998520469904 91 107.75 NA NA 0.998906616892231 NA 92 107.83 NA NA 0.998259138901315 NA 93 107.8 NA NA 0.999681030440858 NA 94 107.81 NA NA 1.00097673265204 NA 95 107.86 NA NA 1.00120221019768 NA 96 107.83 NA NA 1.00082180148054 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/1f84l1292355544.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/1f84l1292355544.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/28h3o1292355544.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/28h3o1292355544.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/38h3o1292355544.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/38h3o1292355544.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/4ir3r1292355544.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t12923554499x70fzgps4bu8yb/4ir3r1292355544.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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