Eigen reeks: prijs tafelbier Classical Deomposition

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 05 Jun 2009 13:29:27 -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/05/t1244230220j6hxks4qe24g57n.htm/, Retrieved Fri, 05 Jun 2009 21:30:20 +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/05/t1244230220j6hxks4qe24g57n.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 «

0.58 0.58 0.59 0.6 0.6 0.61 0.62 0.61 0.62 0.62 0.62 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.64 0.63 0.63 0.63 0.63 0.63 0.64 0.65 0.65 0.65 0.65 0.65 0.66 0.65 0.66 0.66 0.66 0.66 0.68 0.69 0.7 0.71 0.71 0.7 0.7 0.7 0.7 0.71 0.7 0.7 0.7 0.69 0.7 0.69 0.69 0.69 0.7 0.7 0.71 0.71 0.71 0.72 0.73 0.74 0.74 0.74 0.74 0.75 0.75 0.76 0.76 0.76 0.76 0.76 0.77 0.77 0.78 0.78 0.78 0.78 0.78 0.78 0.78 0.8 0.8 0.8 0.81 0.81 0.81 0.8 0.81 0.81 0.81 0.8 0.82 0.83 0.83

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 0.58 NA NA -0.00375992063492064 NA 2 0.58 NA NA 0.00249007936507937 NA 3 0.59 NA NA 0.00308531746031743 NA 4 0.6 NA NA 0.00510912698412697 NA 5 0.6 NA NA 0.00124007936507939 NA 6 0.61 NA NA 0.000228174603174601 NA 7 0.62 0.608621031746032 0.60875 -0.000128968253968249 0.0113789682539682 8 0.61 0.61296626984127 0.612916666666667 4.9603174603144e-05 -0.00296626984126991 9 0.62 0.614037698412698 0.616666666666667 -0.00262896825396826 0.0059623015873016 10 0.62 0.617251984126984 0.619583333333333 -0.00233134920634921 0.00274801587301587 11 0.62 0.621597222222222 0.622083333333333 -0.000486111111111083 -0.00159722222222225 12 0.63 0.621299603174603 0.624166666666667 -0.00286706349206346 0.00870039682539692 13 0.63 0.621656746031746 0.625416666666667 -0.00375992063492064 0.00834325396825397 14 0.63 0.629573412698413 0.627083333333333 0.00249007936507937 0.0004265873015874 15 0.63 0.631835317460317 0.62875 0.00308531746031743 -0.0018353174603174 16 0.63 0.63469246031746 0.629583333333333 0.00510912698412697 -0.00469246031746029 17 0.63 0.631656746031746 0.630416666666667 0.00124007936507939 -0.00165674603174604 18 0.63 0.631061507936508 0.630833333333333 0.000228174603174601 -0.00106150793650783 19 0.63 0.630704365079365 0.630833333333333 -0.000128968253968249 -0.000704365079364999 20 0.64 0.631299603174603 0.63125 4.9603174603144e-05 0.00870039682539692 21 0.63 0.629871031746032 0.6325 -0.00262896825396826 0.000128968253968353 22 0.63 0.631835317460317 0.634166666666667 -0.00233134920634921 -0.0018353174603174 23 0.63 0.635347222222222 0.635833333333333 -0.000486111111111083 -0.00534722222222217 24 0.63 0.634632936507937 0.6375 -0.00286706349206346 -0.0046329365079365 25 0.63 0.635406746031746 0.639166666666667 -0.00375992063492064 -0.00540674603174607 26 0.64 0.643323412698413 0.640833333333333 0.00249007936507937 -0.00332341269841263 27 0.65 0.645585317460317 0.6425 0.00308531746031743 0.00441468253968258 28 0.65 0.64969246031746 0.644583333333333 0.00510912698412697 0.000307539682539604 29 0.65 0.648323412698413 0.647083333333333 0.00124007936507939 0.00167658730158726 30 0.65 0.649811507936508 0.649583333333333 0.000228174603174601 0.000188492063492030 31 0.65 0.651954365079365 0.652083333333333 -0.000128968253968249 -0.00195436507936519 32 0.66 0.655049603174603 0.655 4.9603174603144e-05 0.00495039682539689 33 0.65 0.655704365079365 0.658333333333333 -0.00262896825396826 -0.00570436507936511 34 0.66 0.659751984126984 0.662083333333333 -0.00233134920634921 0.000248015873015928 35 0.66 0.666180555555556 0.666666666666667 -0.000486111111111083 -0.00618055555555563 36 0.66 0.668799603174603 0.671666666666667 -0.00286706349206346 -0.00879960317460327 37 0.66 0.67249007936508 0.67625 -0.00375992063492064 -0.0124900793650794 38 0.68 0.68249007936508 0.68 0.00249007936507937 -0.00249007936507939 39 0.69 0.686835317460318 0.68375 0.00308531746031743 0.00316468253968238 40 0.7 0.692609126984127 0.6875 0.00510912698412697 0.00739087301587282 41 0.71 0.69249007936508 0.69125 0.00124007936507939 0.0175099206349205 42 0.71 0.695228174603175 0.695 0.000228174603174601 0.0147718253968254 43 0.7 0.698204365079365 0.698333333333333 -0.000128968253968249 0.00179563492063495 44 0.7 0.700882936507936 0.700833333333333 4.9603174603144e-05 -0.000882936507936471 45 0.7 0.699037698412698 0.701666666666667 -0.00262896825396826 0.000962301587301595 46 0.7 0.699335317460318 0.701666666666667 -0.00233134920634921 0.000664682539682437 47 0.71 0.700347222222222 0.700833333333333 -0.000486111111111083 0.00965277777777773 48 0.7 0.696299603174603 0.699166666666667 -0.00286706349206346 0.0037003968253968 49 0.7 0.694156746031746 0.697916666666667 -0.00375992063492064 0.00584325396825391 50 0.7 0.69999007936508 0.6975 0.00249007936507937 9.92063492044615e-06 51 0.69 0.700585317460318 0.6975 0.00308531746031743 -0.0105853174603177 52 0.7 0.703025793650794 0.697916666666667 0.00510912698412697 -0.00302579365079381 53 0.69 0.699573412698413 0.698333333333333 0.00124007936507939 -0.00957341269841272 54 0.69 0.698978174603175 0.69875 0.000228174603174601 -0.00897817460317463 55 0.69 0.699871031746032 0.7 -0.000128968253968249 -0.00987103174603177 56 0.7 0.702132936507937 0.702083333333333 4.9603174603144e-05 -0.00213293650793656 57 0.7 0.702787698412698 0.705416666666667 -0.00262896825396826 -0.00278769841269833 58 0.71 0.706835317460317 0.709166666666667 -0.00233134920634921 0.00316468253968261 59 0.71 0.712430555555556 0.712916666666667 -0.000486111111111083 -0.00243055555555560 60 0.71 0.71421626984127 0.717083333333333 -0.00286706349206346 -0.00421626984126988 61 0.72 0.717906746031746 0.721666666666667 -0.00375992063492064 0.00209325396825388 62 0.73 0.72874007936508 0.72625 0.00249007936507937 0.00125992063492053 63 0.74 0.733918650793651 0.730833333333333 0.00308531746031743 0.00608134920634906 64 0.74 0.740525793650794 0.735416666666667 0.00510912698412697 -0.000525793650793638 65 0.74 0.740823412698413 0.739583333333333 0.00124007936507939 -0.000823412698412573 66 0.74 0.743978174603175 0.74375 0.000228174603174601 -0.00397817460317451 67 0.75 0.747371031746032 0.7475 -0.000128968253968249 0.0026289682539683 68 0.75 0.750882936507936 0.750833333333333 4.9603174603144e-05 -0.00088293650793636 69 0.76 0.751121031746032 0.75375 -0.00262896825396826 0.00887896825396828 70 0.76 0.754335317460317 0.756666666666667 -0.00233134920634921 0.00566468253968255 71 0.76 0.759513888888889 0.76 -0.000486111111111083 0.000486111111110965 72 0.76 0.76046626984127 0.763333333333333 -0.00286706349206346 -0.000466269841269962 73 0.76 0.76249007936508 0.76625 -0.00375992063492064 -0.0024900793650795 74 0.77 0.77124007936508 0.76875 0.00249007936507937 -0.00124007936507942 75 0.77 0.77391865079365 0.770833333333333 0.00308531746031743 -0.00391865079365072 76 0.78 0.777609126984127 0.7725 0.00510912698412697 0.00239087301587304 77 0.78 0.77624007936508 0.775 0.00124007936507939 0.00375992063492059 78 0.78 0.778561507936508 0.778333333333333 0.000228174603174601 0.00143849206349200 79 0.78 0.781537698412698 0.781666666666667 -0.000128968253968249 -0.00153769841269835 80 0.78 0.785049603174603 0.785 4.9603174603144e-05 -0.00504960317460312 81 0.78 0.785704365079365 0.788333333333333 -0.00262896825396826 -0.00570436507936489 82 0.78 0.78891865079365 0.79125 -0.00233134920634921 -0.0089186507936505 83 0.8 0.792847222222222 0.793333333333333 -0.000486111111111083 0.00715277777777812 84 0.8 0.792549603174603 0.795416666666666 -0.00286706349206346 0.00745039682539705 85 0.8 0.794156746031746 0.797916666666667 -0.00375992063492064 0.00584325396825403 86 0.81 0.802906746031746 0.800416666666667 0.00249007936507937 0.00709325396825411 87 0.81 0.805585317460317 0.8025 0.00308531746031743 0.00441468253968258 88 0.81 0.810109126984127 0.805 0.00510912698412697 -0.000109126984126906 89 0.8 0.809156746031746 0.807916666666667 0.00124007936507939 -0.00915674603174599 90 0.81 0.810644841269841 0.810416666666667 0.000228174603174601 -0.000644841269841212 91 0.81 NA NA -0.000128968253968249 NA 92 0.81 NA NA 4.9603174603144e-05 NA 93 0.8 NA NA -0.00262896825396826 NA 94 0.82 NA NA -0.00233134920634921 NA 95 0.83 NA NA -0.000486111111111083 NA 96 0.83 NA NA -0.00286706349206346 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/1vklw1244230162.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/1vklw1244230162.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/2r19v1244230162.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/2r19v1244230162.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/3czao1244230162.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/3czao1244230162.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/44c2b1244230162.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244230220j6hxks4qe24g57n/44c2b1244230162.ps (open in new window)

Parameters (Session):

par1 = 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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