Opdracht 9 oef 2

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 15 Dec 2010 17:46:44 +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/15/t1292435401c13slq4l6el096x.htm/, Retrieved Wed, 15 Dec 2010 18:50:06 +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/15/t1292435401c13slq4l6el096x.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 «

78.1 66.7 79 65.2 66.5 77.2 80.2 77.9 78 86.8 92.9 185.8 91 79.1 84.2 70.1 71.3 79.6 92.3 78.7 82.5 98.2 115.4 205.6 94 83.2 80.3 70.4 71.1 78.8 86.3 77.5 80.1 89.8 99.9 218 85.4 77.5 78.6 68.8 64.8 79.8 94.3 79.9 87.5 99.1 109.9 273.6 91.3 80.6 80.4 71.8 75.5 86.6 91.5 86.8 84.6 88.6 102.1 260.3 79 70.6 79.3 66.8 61.2 72.5 83.5 75.8 83.4 89.4 104.9 251.6 80 76.3 81.1 63.1 63.5 78.8 91.7 83.8 83.8 95.8 108.9 258.2 88.7 79.5 74.3 70.5 59.1 73.2 81.2 75 74.6 89.5 107 246.4 83.6 72.1 68.7 60.1 61.1 72.7 85.3 71.4 75.2 89.8 100.9 222.7

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 3 seconds R Server 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 78.1 NA NA -8.08424479166667 NA 2 66.7 NA NA -17.339453125 NA 3 79 NA NA -16.291015625 NA 4 65.2 NA NA -26.9545572916667 NA 5 66.5 NA NA -28.7618489583333 NA 6 77.2 NA NA -17.195703125 NA 7 80.2 79.4928385416667 86.7291666666667 -7.236328125 0.707161458333331 8 77.9 72.290234375 87.7833333333333 -15.4930989583333 5.60976562499999 9 78 75.4365885416667 88.5166666666667 -13.080078125 2.56341145833331 10 86.8 86.2751302083334 88.9375 -2.66236979166667 0.524869791666646 11 92.9 99.708984375 89.3416666666667 10.3673177083333 -6.80898437500001 12 185.8 232.373046875 89.6416666666667 142.731380208333 -46.573046875 13 91 82.1615885416667 90.2458333333333 -8.08424479166667 8.83841145833333 14 79.1 73.4438802083333 90.7833333333333 -17.339453125 5.65611979166665 15 84.2 74.7131510416667 91.0041666666667 -16.291015625 9.48684895833334 16 70.1 64.712109375 91.6666666666667 -26.9545572916667 5.38789062499998 17 71.3 64.3173177083333 93.0791666666667 -28.7618489583333 6.98268229166665 18 79.6 77.6459635416667 94.8416666666667 -17.195703125 1.95403645833332 19 92.3 88.5553385416667 95.7916666666667 -7.236328125 3.74466145833334 20 78.7 80.5944010416667 96.0875 -15.4930989583333 -1.89440104166667 21 82.5 83.0157552083333 96.0958333333333 -13.080078125 -0.515755208333346 22 98.2 93.2834635416667 95.9458333333333 -2.66236979166667 4.91653645833333 23 115.4 106.317317708333 95.95 10.3673177083333 9.08268229166669 24 205.6 238.639713541667 95.9083333333333 142.731380208333 -33.0397135416667 25 94 87.5407552083333 95.625 -8.08424479166667 6.45924479166666 26 83.2 77.985546875 95.325 -17.339453125 5.21445312499999 27 80.3 78.883984375 95.175 -16.291015625 1.416015625 28 70.4 67.7704427083333 94.725 -26.9545572916667 2.62955729166667 29 71.1 64.9673177083333 93.7291666666667 -28.7618489583333 6.13268229166667 30 78.8 76.404296875 93.6 -17.195703125 2.39570312500001 31 86.3 86.5220052083333 93.7583333333333 -7.236328125 -0.222005208333343 32 77.5 77.6694010416667 93.1625 -15.4930989583333 -0.16940104166666 33 80.1 79.7740885416667 92.8541666666667 -13.080078125 0.325911458333337 34 89.8 90.054296875 92.7166666666667 -2.66236979166667 -0.254296874999994 35 99.9 102.754817708333 92.3875 10.3673177083333 -2.85481770833331 36 218 234.898046875 92.1666666666666 142.731380208333 -16.8980468750000 37 85.4 84.457421875 92.5416666666667 -8.08424479166667 0.942578125000011 38 77.5 75.635546875 92.975 -17.339453125 1.86445312500001 39 78.6 77.0923177083333 93.3833333333333 -16.291015625 1.50768229166665 40 68.8 67.124609375 94.0791666666667 -26.9545572916667 1.67539062500001 41 64.8 66.121484375 94.8833333333333 -28.7618489583333 -1.32148437499998 42 79.8 80.4209635416667 97.6166666666667 -17.195703125 -0.620963541666654 43 94.3 92.9428385416667 100.179166666667 -7.236328125 1.35716145833332 44 79.9 85.0610677083333 100.554166666667 -15.4930989583333 -5.16106770833333 45 87.5 87.6782552083333 100.758333333333 -13.080078125 -0.17825520833334 46 99.1 98.2959635416667 100.958333333333 -2.66236979166667 0.804036458333329 47 109.9 111.896484375 101.529166666667 10.3673177083333 -1.99648437500001 48 273.6 244.989713541667 102.258333333333 142.731380208333 28.6102864583334 49 91.3 94.3407552083333 102.425 -8.08424479166667 -3.04075520833332 50 80.6 85.2563802083333 102.595833333333 -17.339453125 -4.65638020833333 51 80.4 86.471484375 102.7625 -16.291015625 -6.071484375 52 71.8 75.249609375 102.204166666667 -26.9545572916667 -3.44960937499999 53 75.5 72.6798177083333 101.441666666667 -28.7618489583333 2.82018229166667 54 86.6 83.366796875 100.5625 -17.195703125 3.23320312499999 55 91.5 92.2595052083333 99.4958333333333 -7.236328125 -0.759505208333337 56 86.8 83.0735677083333 98.5666666666667 -15.4930989583333 3.72643229166667 57 84.6 85.0240885416667 98.1041666666667 -13.080078125 -0.424088541666663 58 88.6 95.1876302083333 97.85 -2.66236979166667 -6.58763020833334 59 102.1 107.413151041667 97.0458333333333 10.3673177083333 -5.31315104166667 60 260.3 238.593880208333 95.8625 142.731380208333 21.7061197916667 61 79 86.857421875 94.9416666666667 -8.08424479166667 -7.857421875 62 70.6 76.810546875 94.15 -17.339453125 -6.21054687499998 63 79.3 77.3506510416667 93.6416666666667 -16.291015625 1.94934895833336 64 66.8 66.6704427083333 93.625 -26.9545572916667 0.129557291666657 65 61.2 65.0131510416667 93.775 -28.7618489583333 -3.81315104166667 66 72.5 76.3334635416666 93.5291666666667 -17.195703125 -3.83346354166666 67 83.5 85.9720052083333 93.2083333333333 -7.236328125 -2.47200520833333 68 75.8 77.9944010416666 93.4875 -15.4930989583333 -2.19440104166665 69 83.4 80.719921875 93.8 -13.080078125 2.68007812500002 70 89.4 91.0584635416667 93.7208333333333 -2.66236979166667 -1.65846354166665 71 104.9 104.029817708333 93.6625 10.3673177083333 0.870182291666694 72 251.6 236.752213541667 94.0208333333333 142.731380208333 14.8477864583334 73 80 86.5407552083334 94.625 -8.08424479166667 -6.54075520833335 74 76.3 77.960546875 95.3 -17.339453125 -1.66054687500001 75 81.1 79.358984375 95.65 -16.291015625 1.74101562500000 76 63.1 68.9787760416666 95.9333333333333 -26.9545572916667 -5.87877604166664 77 63.5 67.6048177083333 96.3666666666667 -28.7618489583333 -4.10481770833333 78 78.8 79.6126302083333 96.8083333333333 -17.195703125 -0.812630208333317 79 91.7 90.2095052083333 97.4458333333333 -7.236328125 1.49049479166668 80 83.8 82.4485677083333 97.9416666666666 -15.4930989583333 1.35143229166668 81 83.8 84.7115885416667 97.7916666666667 -13.080078125 -0.91158854166666 82 95.8 95.154296875 97.8166666666667 -2.66236979166667 0.645703124999997 83 108.9 108.308984375 97.9416666666667 10.3673177083333 0.591015625000011 84 258.2 240.256380208333 97.525 142.731380208333 17.9436197916667 85 88.7 88.769921875 96.8541666666667 -8.08424479166667 -0.0699218750000057 86 79.5 78.710546875 96.05 -17.339453125 0.789453125000009 87 74.3 79.008984375 95.3 -16.291015625 -4.70898437499999 88 70.5 67.699609375 94.6541666666667 -26.9545572916667 2.80039062500001 89 59.1 65.5506510416667 94.3125 -28.7618489583333 -6.45065104166666 90 73.2 76.5459635416667 93.7416666666666 -17.195703125 -3.34596354166663 91 81.2 85.801171875 93.0375 -7.236328125 -4.60117187499999 92 75 77.0235677083333 92.5166666666667 -15.4930989583333 -2.02356770833332 93 74.6 78.894921875 91.975 -13.080078125 -4.294921875 94 89.5 88.6459635416667 91.3083333333333 -2.66236979166667 0.85403645833334 95 107 101.325651041667 90.9583333333333 10.3673177083333 5.67434895833334 96 246.4 233.752213541667 91.0208333333333 142.731380208333 12.6477864583334 97 83.6 83.0865885416667 91.1708333333333 -8.08424479166667 0.513411458333323 98 72.1 73.8522135416667 91.1916666666667 -17.339453125 -1.75221354166666 99 68.7 74.7756510416667 91.0666666666667 -16.291015625 -6.07565104166666 100 60.1 64.149609375 91.1041666666667 -26.9545572916667 -4.049609375 101 61.1 62.1006510416667 90.8625 -28.7618489583333 -1.00065104166666 102 72.7 72.4251302083333 89.6208333333334 -17.195703125 0.27486979166666 103 85.3 NA NA -7.236328125 NA 104 71.4 NA NA -15.4930989583333 NA 105 75.2 NA NA -13.080078125 NA 106 89.8 NA NA -2.66236979166667 NA 107 100.9 NA NA 10.3673177083333 NA 108 222.7 NA NA 142.731380208333 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/1go961292435201.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/1go961292435201.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/2go961292435201.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/2go961292435201.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/38f891292435201.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/38f891292435201.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/48f891292435201.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/15/t1292435401c13slq4l6el096x/48f891292435201.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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