*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 13 Dec 2010 12:49:59 +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/13/t1292244578tahgfaafgujydx6.htm/, Retrieved Mon, 13 Dec 2010 13:49:38 +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/13/t1292244578tahgfaafgujydx6.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 «

3.65 3.59 3.31 3.89 4.31 4.35 4.11 3.90 3.75 3.75 3.88 3.93 3.97 3.97 4.33 4.16 4.93 3.86 4.06 4.18 4.08 4.38 4.48 4.41 4.37 4.56 4.71 4.94 5.03 5.08 5.05 4.83 4.68 4.69 4.58 4.54 4.75 4.71 4.50 4.62 4.69 5.05 4.93 4.53 4.33 4.33 3.87 3.74 3.31 3.21 2.93 3.19 3.46 3.73 3.60 3.46 3.25 3.19 2.82 1.89 1.98 2.30 2.42 2.47 2.81 3.37 3.14 3.21 3.02 2.96 2.92 3.07

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 3.65 NA NA -0.282993055555555 NA 2 3.59 NA NA -0.195159722222222 NA 3 3.31 NA NA -0.155326388888889 NA 4 3.89 NA NA -0.0446597222222221 NA 5 4.31 NA NA 0.277923611111112 NA 6 4.35 NA NA 0.327090277777777 NA 7 4.11 4.14934027777778 3.88166666666667 0.267673611111111 -0.0393402777777774 8 3.9 4.03317361111111 3.91083333333333 0.122340277777778 -0.133173611111111 9 3.75 3.94767361111111 3.96916666666667 -0.0214930555555556 -0.197673611111111 10 3.75 4.07067361111111 4.02291666666667 0.0477569444444444 -0.320673611111112 11 3.88 3.99009027777778 4.06 -0.069909722222222 -0.110090277777778 12 3.93 3.79217361111111 4.06541666666667 -0.273243055555556 0.137826388888890 13 3.97 3.75992361111111 4.04291666666667 -0.282993055555555 0.21007638888889 14 3.97 3.85734027777778 4.0525 -0.195159722222222 0.112659722222222 15 4.33 3.92259027777778 4.07791666666667 -0.155326388888889 0.407409722222222 16 4.16 4.07325694444444 4.11791666666667 -0.0446597222222221 0.086743055555556 17 4.93 4.44709027777778 4.16916666666667 0.277923611111112 0.482909722222222 18 3.86 4.54125694444445 4.21416666666667 0.327090277777777 -0.681256944444445 19 4.06 4.51850694444444 4.25083333333333 0.267673611111111 -0.458506944444444 20 4.18 4.41442361111111 4.29208333333333 0.122340277777778 -0.234423611111112 21 4.08 4.31100694444444 4.3325 -0.0214930555555556 -0.231006944444444 22 4.38 4.42859027777778 4.38083333333333 0.0477569444444444 -0.0485902777777776 23 4.48 4.34759027777778 4.4175 -0.069909722222222 0.132409722222223 24 4.41 4.19925694444444 4.4725 -0.273243055555556 0.210743055555556 25 4.37 4.28159027777778 4.56458333333333 -0.282993055555555 0.088409722222222 26 4.56 4.43775694444444 4.63291666666667 -0.195159722222222 0.122243055555556 27 4.71 4.52967361111111 4.685 -0.155326388888889 0.180326388888888 28 4.94 4.67825694444444 4.72291666666667 -0.0446597222222221 0.261743055555556 29 5.03 5.01792361111111 4.74 0.277923611111112 0.0120763888888895 30 5.08 5.07667361111111 4.74958333333333 0.327090277777777 0.00332638888888859 31 5.05 5.03850694444444 4.77083333333333 0.267673611111111 0.0114930555555564 32 4.83 4.91525694444445 4.79291666666667 0.122340277777778 -0.0852569444444455 33 4.68 4.76892361111111 4.79041666666667 -0.0214930555555556 -0.0889236111111122 34 4.69 4.81609027777778 4.76833333333333 0.0477569444444444 -0.126090277777777 35 4.58 4.67092361111111 4.74083333333333 -0.069909722222222 -0.0909236111111111 36 4.54 4.45217361111111 4.72541666666667 -0.273243055555556 0.087826388888888 37 4.75 4.43617361111111 4.71916666666667 -0.282993055555555 0.313826388888889 38 4.71 4.50650694444444 4.70166666666667 -0.195159722222222 0.203493055555557 39 4.5 4.51925694444444 4.67458333333333 -0.155326388888889 -0.0192569444444448 40 4.62 4.60034027777778 4.645 -0.0446597222222221 0.0196597222222215 41 4.69 4.87834027777778 4.60041666666667 0.277923611111112 -0.188340277777777 42 5.05 4.86459027777778 4.5375 0.327090277777777 0.185409722222222 43 4.93 4.71184027777778 4.44416666666667 0.267673611111111 0.218159722222222 44 4.53 4.44400694444444 4.32166666666667 0.122340277777778 0.085993055555556 45 4.33 4.17225694444444 4.19375 -0.0214930555555556 0.157743055555556 46 4.33 4.11650694444444 4.06875 0.0477569444444444 0.213493055555556 47 3.87 3.88800694444444 3.95791666666667 -0.069909722222222 -0.0180069444444442 48 3.74 3.57842361111111 3.85166666666667 -0.273243055555556 0.161576388888890 49 3.31 3.45825694444444 3.74125 -0.282993055555555 -0.148256944444444 50 3.21 3.44609027777778 3.64125 -0.195159722222222 -0.236090277777778 51 2.93 3.39634027777778 3.55166666666667 -0.155326388888889 -0.466340277777777 52 3.19 3.41450694444444 3.45916666666667 -0.0446597222222221 -0.224506944444444 53 3.46 3.64584027777778 3.36791666666667 0.277923611111112 -0.185840277777778 54 3.73 3.57417361111111 3.24708333333333 0.327090277777777 0.155826388888889 55 3.6 3.38225694444444 3.11458333333333 0.267673611111111 0.217743055555556 56 3.46 3.14359027777778 3.02125 0.122340277777778 0.316409722222223 57 3.25 2.94059027777778 2.96208333333333 -0.0214930555555556 0.309409722222223 58 3.19 2.95859027777778 2.91083333333333 0.0477569444444444 0.231409722222223 59 2.82 2.78384027777778 2.85375 -0.069909722222222 0.0361597222222225 60 1.89 2.53842361111111 2.81166666666667 -0.273243055555556 -0.648423611111111 61 1.98 2.49450694444444 2.7775 -0.282993055555555 -0.514506944444444 62 2.3 2.55275694444444 2.74791666666667 -0.195159722222222 -0.252756944444444 63 2.42 2.57259027777778 2.72791666666667 -0.155326388888889 -0.152590277777777 64 2.47 2.66409027777778 2.70875 -0.0446597222222221 -0.194090277777777 65 2.81 2.98125694444444 2.70333333333333 0.277923611111112 -0.171256944444444 66 3.37 3.08375694444444 2.75666666666667 0.327090277777777 0.286243055555556 67 3.14 NA NA 0.267673611111111 NA 68 3.21 NA NA 0.122340277777778 NA 69 3.02 NA NA -0.0214930555555556 NA 70 2.96 NA NA 0.0477569444444444 NA 71 2.92 NA NA -0.069909722222222 NA 72 3.07 NA NA -0.273243055555556 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/1c83t1292244595.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/1c83t1292244595.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/2c83t1292244595.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/2c83t1292244595.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/3n02e1292244595.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/3n02e1292244595.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/4n02e1292244595.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/13/t1292244578tahgfaafgujydx6/4n02e1292244595.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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