decompositie- zakje friet - Keshia Vleminx

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 24 May 2010 20:20:37 +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/May/24/t1274732904t40j6333j1wqcqd.htm/, Retrieved Mon, 24 May 2010 22:28:30 +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/2010/May/24/t1274732904t40j6333j1wqcqd.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 «

2.06 2.06 2.05 2.04 2.04 2.03 2.03 2.03 2.02 2.02 2.02 2.02 2.01 2.01 2.01 2 2 1.99 1.99 1.99 1.98 1.97 1.97 1.96 1.96 1.96 1.96 1.95 1.94 1.94 1.93 1.93 1.93 1.92 1.92 1.9 1.9 1.9 1.9 1.89 1.88 1.88 1.87 1.86 1.86 1.85 1.83 1.82 1.8 1.8 1.79 1.78 1.78 1.78 1.77 1.77 1.76 1.75 1.75 1.75 1.75 1.75 1.74 1.74 1.74 1.74 1.73 1.73 1.73 1.73 1.73 1.72 1.71 1.71 1.71 1.7 1.7 1.7 1.7 1.7 1.69 1.68 1.67 1.65 1.61

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 2.06 NA NA -0.00437500000000002 NA 2 2.06 NA NA 0.000208333333333326 NA 3 2.05 NA NA 0.00145833333333345 NA 4 2.04 NA NA -0.00222222222222217 NA 5 2.04 NA NA -0.000763888888888826 NA 6 2.03 NA NA 0.00256944444444444 NA 7 2.03 2.03416666666667 2.03291666666667 0.00125000000000001 -0.00416666666666687 8 2.03 2.03020833333333 2.02875 0.00145833333333323 -0.000208333333333588 9 2.02 2.02798611111111 2.025 0.00298611111111102 -0.0079861111111108 10 2.02 2.02111111111111 2.02166666666667 -0.000555555555555608 -0.00111111111111128 11 2.02 2.01916666666667 2.01833333333333 0.00083333333333335 0.00083333333333302 12 2.02 2.01215277777778 2.015 -0.00284722222222219 0.0078472222222219 13 2.01 2.00729166666667 2.01166666666667 -0.00437500000000002 0.00270833333333265 14 2.01 2.00854166666667 2.00833333333333 0.000208333333333326 0.00145833333333334 15 2.01 2.00645833333333 2.005 0.00145833333333345 0.00354166666666655 16 2 1.99902777777778 2.00125 -0.00222222222222217 0.000972222222222374 17 2 1.99631944444444 1.99708333333333 -0.000763888888888826 0.00368055555555524 18 1.99 1.99506944444444 1.9925 0.00256944444444444 -0.00506944444444435 19 1.99 1.98916666666667 1.98791666666667 0.00125000000000001 0.000833333333333464 20 1.99 1.98520833333333 1.98375 0.00145833333333323 0.00479166666666697 21 1.98 1.98256944444444 1.97958333333333 0.00298611111111102 -0.00256944444444418 22 1.97 1.97486111111111 1.97541666666667 -0.000555555555555608 -0.00486111111111098 23 1.97 1.97166666666667 1.97083333333333 0.00083333333333335 -0.00166666666666626 24 1.96 1.96340277777778 1.96625 -0.00284722222222219 -0.00340277777777764 25 1.96 1.95729166666667 1.96166666666667 -0.00437500000000002 0.00270833333333353 26 1.96 1.956875 1.95666666666667 0.000208333333333326 0.00312500000000004 27 1.96 1.95354166666667 1.95208333333333 0.00145833333333345 0.00645833333333345 28 1.95 1.94569444444444 1.94791666666667 -0.00222222222222217 0.00430555555555556 29 1.94 1.94298611111111 1.94375 -0.000763888888888826 -0.00298611111111091 30 1.94 1.94173611111111 1.93916666666667 0.00256944444444444 -0.00173611111111094 31 1.93 1.93541666666667 1.93416666666667 0.00125000000000001 -0.00541666666666663 32 1.93 1.930625 1.92916666666667 0.00145833333333323 -0.000624999999999876 33 1.93 1.92715277777778 1.92416666666667 0.00298611111111102 0.00284722222222267 34 1.92 1.91861111111111 1.91916666666667 -0.000555555555555608 0.00138888888888888 35 1.92 1.915 1.91416666666667 0.00083333333333335 0.00500000000000012 36 1.9 1.90631944444444 1.90916666666667 -0.00284722222222219 -0.00631944444444454 37 1.9 1.89979166666667 1.90416666666667 -0.00437500000000002 0.000208333333333366 38 1.9 1.89895833333333 1.89875 0.000208333333333326 0.00104166666666683 39 1.9 1.894375 1.89291666666667 0.00145833333333345 0.00562500000000044 40 1.89 1.88486111111111 1.88708333333333 -0.00222222222222217 0.00513888888888925 41 1.88 1.87965277777778 1.88041666666667 -0.000763888888888826 0.000347222222222499 42 1.88 1.87590277777778 1.87333333333333 0.00256944444444444 0.00409722222222242 43 1.87 1.86708333333333 1.86583333333333 0.00125000000000001 0.0029166666666669 44 1.86 1.85895833333333 1.8575 0.00145833333333323 0.00104166666666705 45 1.86 1.85173611111111 1.84875 0.00298611111111102 0.00826388888888929 46 1.85 1.83902777777778 1.83958333333333 -0.000555555555555608 0.0109722222222222 47 1.83 1.83166666666667 1.83083333333333 0.00083333333333335 -0.00166666666666648 48 1.82 1.81965277777778 1.8225 -0.00284722222222219 0.000347222222222276 49 1.8 1.80979166666667 1.81416666666667 -0.00437500000000002 -0.00979166666666664 50 1.8 1.80645833333333 1.80625 0.000208333333333326 -0.00645833333333323 51 1.79 1.79979166666667 1.79833333333333 0.00145833333333345 -0.00979166666666642 52 1.78 1.78777777777778 1.79 -0.00222222222222217 -0.00777777777777766 53 1.78 1.78173611111111 1.7825 -0.000763888888888826 -0.00173611111111072 54 1.78 1.77881944444444 1.77625 0.00256944444444444 0.00118055555555596 55 1.77 1.7725 1.77125 0.00125000000000001 -0.00249999999999972 56 1.77 1.76854166666667 1.76708333333333 0.00145833333333323 0.00145833333333356 57 1.76 1.76590277777778 1.76291666666667 0.00298611111111102 -0.00590277777777781 58 1.75 1.75861111111111 1.75916666666667 -0.000555555555555608 -0.00861111111111068 59 1.75 1.75666666666667 1.75583333333333 0.00083333333333335 -0.00666666666666615 60 1.75 1.74965277777778 1.7525 -0.00284722222222219 0.000347222222222499 61 1.75 1.74479166666667 1.74916666666667 -0.00437500000000002 0.0052083333333337 62 1.75 1.74604166666667 1.74583333333333 0.000208333333333326 0.00395833333333351 63 1.74 1.744375 1.74291666666667 0.00145833333333345 -0.00437499999999957 64 1.74 1.73861111111111 1.74083333333333 -0.00222222222222217 0.00138888888888888 65 1.74 1.73840277777778 1.73916666666667 -0.000763888888888826 0.00159722222222225 66 1.74 1.73965277777778 1.73708333333333 0.00256944444444444 0.000347222222222276 67 1.73 1.73541666666667 1.73416666666667 0.00125000000000001 -0.00541666666666663 68 1.73 1.73229166666667 1.73083333333333 0.00145833333333323 -0.00229166666666658 69 1.73 1.73090277777778 1.72791666666667 0.00298611111111102 -0.000902777777777475 70 1.73 1.72444444444444 1.725 -0.000555555555555608 0.00555555555555576 71 1.73 1.7225 1.72166666666667 0.00083333333333335 0.00750000000000028 72 1.72 1.71548611111111 1.71833333333333 -0.00284722222222219 0.00451388888888959 73 1.71 1.71104166666667 1.71541666666667 -0.00437500000000002 -0.00104166666666594 74 1.71 1.713125 1.71291666666667 0.000208333333333326 -0.00312499999999982 75 1.71 1.71145833333333 1.71 0.00145833333333345 -0.00145833333333312 76 1.7 1.70402777777778 1.70625 -0.00222222222222217 -0.00402777777777796 77 1.7 1.70090277777778 1.70166666666667 -0.000763888888888826 -0.000902777777777919 78 1.7 1.69881944444444 1.69625 0.00256944444444444 0.00118055555555552 79 1.7 1.69041666666667 1.68916666666667 0.00125000000000001 0.0095833333333335 80 1.7 NA NA 0.00145833333333323 NA 81 1.69 NA NA 0.00298611111111102 NA 82 1.68 NA NA -0.000555555555555608 NA 83 1.67 NA NA 0.00083333333333335 NA 84 1.65 NA NA -0.00284722222222219 NA 85 1.61 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/1jx7k1274732435.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/1jx7k1274732435.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/2c6o51274732435.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/2c6o51274732435.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/3c6o51274732435.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/3c6o51274732435.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/45f581274732435.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/24/t1274732904t40j6333j1wqcqd/45f581274732435.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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