decompositie-financiële situatie Belgische gezinnen-Robin Sluyts

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 01 Jun 2009 11:49:12 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc.htm/, Retrieved Mon, 01 Jun 2009 19:50:04 +0200

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/2009/Jun/01/t12438786004cpw6yy638zcqnc.htm/}, year = {2009}, } @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 = {2009}, 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:

Dataseries X:

» Textbox « » Textfile « » CSV «

1 -1 3 4 3 2 1 4 3 5 6 6 6 6 6 5 6 5 6 5 7 4 5 6 6 5 3 2 3 3 2 0 4 4 5 6 6 5 5 3 5 5 5 3 6 6 4 6 5 4 5 5 4 3 2 3 2 -1 0 -2 1 -2 -2 -2 -6 -4 -2 0 -5 -4 -5 -1

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 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1 NA NA 1.34652777777778 NA 2 -1 NA NA 0.204861111111111 NA 3 3 NA NA 0.104861111111111 NA 4 4 NA NA -0.553472222222222 NA 5 3 NA NA -0.586805555555556 NA 6 2 NA NA -0.436805555555556 NA 7 1 2.56319444444444 3.29166666666667 -0.728472222222222 -1.56319444444444 8 4 2.87152777777778 3.79166666666667 -0.920138888888889 1.12847222222222 9 3 4.73819444444444 4.20833333333333 0.529861111111111 -1.73819444444444 10 5 4.19652777777778 4.375 -0.178472222222222 0.803472222222222 11 6 4.88819444444444 4.54166666666667 0.346527777777778 1.11180555555556 12 6 5.66319444444444 4.79166666666667 0.871527777777778 0.336805555555556 13 6 6.47152777777778 5.125 1.34652777777778 -0.471527777777778 14 6 5.57986111111111 5.375 0.204861111111111 0.420138888888888 15 6 5.68819444444444 5.58333333333333 0.104861111111111 0.311805555555556 16 5 5.15486111111111 5.70833333333333 -0.553472222222222 -0.154861111111111 17 6 5.03819444444444 5.625 -0.586805555555556 0.961805555555555 18 5 5.14652777777778 5.58333333333333 -0.436805555555556 -0.146527777777777 19 6 4.85486111111111 5.58333333333333 -0.728472222222222 1.14513888888889 20 5 4.62152777777778 5.54166666666667 -0.920138888888889 0.378472222222222 21 7 5.90486111111111 5.375 0.529861111111111 1.09513888888889 22 4 4.94652777777778 5.125 -0.178472222222222 -0.946527777777777 23 5 5.22152777777778 4.875 0.346527777777778 -0.221527777777778 24 6 5.53819444444444 4.66666666666667 0.871527777777778 0.461805555555557 25 6 5.76319444444444 4.41666666666667 1.34652777777778 0.236805555555555 26 5 4.24652777777778 4.04166666666667 0.204861111111111 0.753472222222222 27 3 3.81319444444444 3.70833333333333 0.104861111111111 -0.813194444444444 28 2 3.02986111111111 3.58333333333333 -0.553472222222222 -1.02986111111111 29 3 2.99652777777778 3.58333333333333 -0.586805555555556 0.00347222222222232 30 3 3.14652777777778 3.58333333333333 -0.436805555555556 -0.146527777777778 31 2 2.85486111111111 3.58333333333333 -0.728472222222222 -0.85486111111111 32 0 2.66319444444444 3.58333333333333 -0.920138888888889 -2.66319444444444 33 4 4.19652777777778 3.66666666666667 0.529861111111111 -0.196527777777778 34 4 3.61319444444444 3.79166666666667 -0.178472222222222 0.386805555555555 35 5 4.26319444444444 3.91666666666667 0.346527777777778 0.736805555555556 36 6 4.95486111111111 4.08333333333333 0.871527777777778 1.04513888888889 37 6 5.63819444444444 4.29166666666667 1.34652777777778 0.361805555555556 38 5 4.74652777777778 4.54166666666667 0.204861111111111 0.253472222222222 39 5 4.85486111111111 4.75 0.104861111111111 0.145138888888889 40 3 4.36319444444444 4.91666666666667 -0.553472222222222 -1.36319444444444 41 5 4.37152777777778 4.95833333333333 -0.586805555555556 0.628472222222223 42 5 4.47986111111111 4.91666666666667 -0.436805555555556 0.52013888888889 43 5 4.14652777777778 4.875 -0.728472222222222 0.853472222222222 44 3 3.87152777777778 4.79166666666667 -0.920138888888889 -0.871527777777777 45 6 5.27986111111111 4.75 0.529861111111111 0.72013888888889 46 6 4.65486111111111 4.83333333333333 -0.178472222222222 1.34513888888889 47 4 5.22152777777778 4.875 0.346527777777778 -1.22152777777778 48 6 5.62152777777778 4.75 0.871527777777778 0.378472222222222 49 5 5.88819444444444 4.54166666666667 1.34652777777778 -0.888194444444445 50 4 4.62152777777778 4.41666666666667 0.204861111111111 -0.621527777777777 51 5 4.35486111111111 4.25 0.104861111111111 0.645138888888889 52 5 3.23819444444444 3.79166666666667 -0.553472222222222 1.76180555555556 53 4 2.74652777777778 3.33333333333333 -0.586805555555556 1.25347222222222 54 3 2.39652777777778 2.83333333333333 -0.436805555555556 0.603472222222222 55 2 1.60486111111111 2.33333333333333 -0.728472222222222 0.395138888888889 56 3 0.996527777777777 1.91666666666667 -0.920138888888889 2.00347222222222 57 2 1.90486111111111 1.375 0.529861111111111 0.0951388888888889 58 -1 0.613194444444444 0.791666666666667 -0.178472222222222 -1.61319444444444 59 0 0.429861111111111 0.0833333333333334 0.346527777777778 -0.429861111111111 60 -2 0.246527777777778 -0.625 0.871527777777778 -2.24652777777778 61 1 0.263194444444444 -1.08333333333333 1.34652777777778 0.736805555555556 62 -2 -1.17013888888889 -1.375 0.204861111111111 -0.829861111111111 63 -2 -1.68680555555556 -1.79166666666667 0.104861111111111 -0.313194444444444 64 -2 -2.76180555555556 -2.20833333333333 -0.553472222222222 0.761805555555555 65 -6 -3.12847222222222 -2.54166666666667 -0.586805555555556 -2.87152777777778 66 -4 -3.14513888888889 -2.70833333333333 -0.436805555555556 -0.854861111111112 67 -2 NA NA -0.728472222222222 NA 68 0 NA NA -0.920138888888889 NA 69 -5 NA NA 0.529861111111111 NA 70 -4 NA NA -0.178472222222222 NA 71 -5 NA NA 0.346527777777778 NA 72 -1 NA NA 0.871527777777778 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/1jd1f1243878549.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/1jd1f1243878549.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/2oruu1243878549.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/2oruu1243878549.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/3tvrs1243878549.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/3tvrs1243878549.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/4nirs1243878549.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438786004cpw6yy638zcqnc/4nirs1243878549.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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