classical decomposition grijze garnalen

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 13 Jan 2010 14:45:45 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1.htm/, Retrieved Wed, 13 Jan 2010 22:49:02 +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/Jan/13/t1263419337ez2n1uv5ci8clz1.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:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

35,75 36,25 35,32 33,80 31,54 30,74 30,55 30,06 30,30 32,24 33,42 33,31 33,76 33,61 33,68 34,17 34,17 34,07 32,36 31,57 31,34 30,81 29,95 29,74 29,56 29,91 29,82 31,46 32,55 32,82 32,74 33,05 32,63 31,85 31,99 31,39 30,16 30,04 29,55 29,12 29,31 29,36 29,67 30,69 31,08 31,08 31,10 30,96 31,94 31,59 32,01 32,13 32,20 32,05 32,12 31,66 32,99 36,02 37,10 37,96 38,96 41,66 47,29 49,42 48,17 46,25 45,43 43,83 41,51 38,25 35,23 34,18

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 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 35.75 NA NA -0.530611111111112 NA 2 36.25 NA NA -0.283361111111111 NA 3 35.32 NA NA 0.616472222222221 NA 4 33.8 NA NA 1.26297222222222 NA 5 31.54 NA NA 1.21780555555556 NA 6 30.74 NA NA 0.825472222222222 NA 7 30.55 32.0082222222222 32.6904166666667 -0.682194444444444 -1.45822222222222 8 30.06 31.6614722222222 32.4975 -0.836027777777776 -1.60147222222223 9 30.3 31.6003055555556 32.3191666666667 -0.71886111111111 -1.30030555555556 10 32.24 32.0494722222222 32.26625 -0.216777777777778 0.190527777777781 11 33.42 32.2177222222222 32.39125 -0.173527777777779 1.20227777777778 12 33.31 32.1582222222222 32.6395833333333 -0.481361111111113 1.15177777777778 13 33.76 32.3231388888889 32.85375 -0.530611111111112 1.43686111111111 14 33.61 32.7087222222222 32.9920833333333 -0.283361111111111 0.901277777777779 15 33.68 33.7148055555556 33.0983333333333 0.616472222222221 -0.0348055555555575 16 34.17 34.3450555555556 33.0820833333333 1.26297222222222 -0.175055555555552 17 34.17 34.0957222222222 32.8779166666667 1.21780555555556 0.0742777777777803 18 34.07 33.4100555555556 32.5845833333333 0.825472222222222 0.659944444444442 19 32.36 31.5786388888889 32.2608333333333 -0.682194444444444 0.781361111111103 20 31.57 31.0956388888889 31.9316666666667 -0.836027777777776 0.474361111111115 21 31.34 30.8978055555556 31.6166666666667 -0.71886111111111 0.442194444444446 22 30.81 31.1261388888889 31.3429166666667 -0.216777777777778 -0.31613888888889 23 29.95 30.9889722222222 31.1625 -0.173527777777779 -1.03897222222222 24 29.74 30.5615555555555 31.0429166666667 -0.481361111111113 -0.821555555555548 25 29.56 30.4760555555556 31.0066666666667 -0.530611111111112 -0.916055555555552 26 29.91 30.8008055555555 31.0841666666667 -0.283361111111111 -0.890805555555545 27 29.82 31.8160555555556 31.1995833333333 0.616472222222221 -1.99605555555555 28 31.46 32.5596388888889 31.2966666666667 1.26297222222222 -1.09963888888889 29 32.55 32.6428055555555 31.425 1.21780555555556 -0.0928055555555538 30 32.82 32.4042222222222 31.57875 0.825472222222222 0.41577777777778 31 32.74 30.9903055555555 31.6725 -0.682194444444444 1.74969444444445 32 33.05 30.8668888888889 31.7029166666667 -0.836027777777776 2.18311111111112 33 32.63 30.9782222222222 31.6970833333333 -0.71886111111111 1.65177777777778 34 31.85 31.3715555555556 31.5883333333333 -0.216777777777778 0.478444444444449 35 31.99 31.1823055555556 31.3558333333333 -0.173527777777779 0.807694444444447 36 31.39 30.5953055555556 31.0766666666667 -0.481361111111113 0.794694444444445 37 30.16 30.2739722222222 30.8045833333333 -0.530611111111112 -0.113972222222213 38 30.04 30.2949722222222 30.5783333333333 -0.283361111111111 -0.254972222222214 39 29.55 31.0318888888889 30.4154166666667 0.616472222222221 -1.48188888888889 40 29.12 31.5817222222222 30.31875 1.26297222222222 -2.46172222222222 41 29.31 31.4673888888889 30.2495833333333 1.21780555555556 -2.15738888888889 42 29.36 31.0200555555556 30.1945833333333 0.825472222222222 -1.66005555555556 43 29.67 29.5686388888889 30.2508333333333 -0.682194444444444 0.101361111111114 44 30.69 29.5535555555556 30.3895833333333 -0.836027777777776 1.13644444444445 45 31.08 29.8378055555556 30.5566666666667 -0.71886111111111 1.24219444444445 46 31.08 30.5678055555556 30.7845833333333 -0.216777777777778 0.512194444444443 47 31.1 30.8568888888889 31.0304166666667 -0.173527777777779 0.243111111111112 48 30.96 30.7815555555556 31.2629166666667 -0.481361111111113 0.178444444444448 49 31.94 30.9464722222222 31.4770833333333 -0.530611111111112 0.993527777777771 50 31.59 31.3362222222222 31.6195833333333 -0.283361111111111 0.253777777777778 51 32.01 32.3560555555555 31.7395833333333 0.616472222222221 -0.346055555555552 52 32.13 33.2879722222222 32.025 1.26297222222222 -1.15797222222222 53 32.2 33.6986388888889 32.4808333333333 1.21780555555556 -1.49863888888888 54 32.05 33.8479722222222 33.0225 0.825472222222222 -1.79797222222223 55 32.12 32.9244722222222 33.6066666666667 -0.682194444444444 -0.804472222222223 56 31.66 33.4827222222222 34.31875 -0.836027777777776 -1.82272222222222 57 32.99 34.6561388888889 35.375 -0.71886111111111 -1.66613888888889 58 36.02 36.5153055555555 36.7320833333333 -0.216777777777778 -0.495305555555547 59 37.1 37.9443888888889 38.1179166666667 -0.173527777777779 -0.844388888888886 60 37.96 38.8936388888889 39.375 -0.481361111111113 -0.933638888888893 61 38.96 39.9906388888889 40.52125 -0.530611111111112 -1.03063888888889 62 41.66 41.2995555555556 41.5829166666667 -0.283361111111111 0.36044444444444 63 47.29 43.0614722222222 42.445 0.616472222222221 4.22852777777778 64 49.42 44.1558888888889 42.8929166666667 1.26297222222222 5.26411111111111 65 48.17 44.1257222222222 42.9079166666667 1.21780555555556 4.04427777777777 66 46.25 43.4979722222222 42.6725 0.825472222222222 2.75202777777778 67 45.43 NA NA -0.682194444444444 NA 68 43.83 NA NA -0.836027777777776 NA 69 41.51 NA NA -0.71886111111111 NA 70 38.25 NA NA -0.216777777777778 NA 71 35.23 NA NA -0.173527777777779 NA 72 34.18 NA NA -0.481361111111113 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/1s9r51263419142.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/1s9r51263419142.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/2z1ca1263419142.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/2z1ca1263419142.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/3zh1t1263419142.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/3zh1t1263419142.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/4by231263419142.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263419337ez2n1uv5ci8clz1/4by231263419142.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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