classical decomposition 9b - Kelly Michielsen - MAR 201b

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 03 Jun 2009 02:02:43 -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/03/t12440161998npvp8p2jcw2s0n.htm/, Retrieved Wed, 03 Jun 2009 10:03:23 +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/03/t12440161998npvp8p2jcw2s0n.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 «

104.9 110.9 104.8 94.1 95.8 99.3 101.1 104.0 99.0 105.4 107.1 110.7 117.1 118.7 126.5 127.5 134.6 131.8 135.9 142.7 141.7 153.4 145.0 137.7 148.3 152.2 169.4 168.6 161.1 174.1 179.0 190.6 190.0 181.6 174.8 180.5 196.8 193.8 197.0 216.3 221.4 217.9 229.7 227.4 204.2 196.6 198.8 207.5 190.7 201.6 210.5 223.5 223.8 231.2 244.0 234.7 250.2 265.7 287.6 283.3 295.4 312.3 333.8 347.7 383.2 407.1 413.6 362.7 321.9 239.4 191.0 159.7 166.7

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 1 104.9 NA NA 0.955656206640385 NA 2 110.9 NA NA 0.95949601360411 NA 3 104.8 NA NA 0.998464941325473 NA 4 94.1 NA NA 1.02127621594823 NA 5 95.8 NA NA 1.03721996947 NA 6 99.3 NA NA 1.05719797800196 NA 7 101.1 112.763815369265 103.6 1.08845381630564 0.896564200749421 8 104 105.871224393949 104.433333333333 1.01376850680449 0.982325467522823 9 99 104.568410338976 105.6625 0.989645430866917 0.94674863736644 10 105.4 105.011318643603 107.958333333333 0.972702295425113 1.00370132821316 11 107.1 106.791801532138 110.966666666667 0.962377304284817 1.00288597498534 12 110.7 107.527526798223 113.9375 0.943741321322859 1.02950382377649 13 117.1 111.564898323543 116.741666666667 0.955656206640385 1.04961329019819 14 118.7 114.951620329829 119.804166666667 0.95949601360411 1.03260832391415 15 126.5 123.006720500709 123.195833333333 0.998464941325473 1.02839909465979 16 127.5 129.676547520026 126.975 1.02127621594823 0.983215565484653 17 134.6 135.413388764181 130.554166666667 1.03721996947 0.99399329141967 18 131.8 140.880440551911 133.258333333333 1.05719797800196 0.935545058516727 19 135.9 147.685041975737 135.683333333333 1.08845381630564 0.920201519273201 20 142.7 140.284441164517 138.379166666667 1.01376850680449 1.01721900743540 21 141.7 140.096681307098 141.5625 0.989645430866917 1.01144437311393 22 153.4 141.102626730106 145.0625 0.972702295425113 1.08715197976730 23 145 142.315553776552 147.879166666667 0.962377304284817 1.01886263414091 24 137.7 142.265071933915 150.745833333333 0.943741321322859 0.96791150581194 25 148.3 147.461734585472 154.304166666667 0.955656206640385 1.00568463009664 26 152.2 151.692321850753 158.095833333333 0.95949601360411 1.00334676233479 27 169.4 161.855327259448 162.104166666667 0.998464941325473 1.04661368191149 28 168.6 168.808447861109 165.291666666667 1.02127621594823 0.998765181104677 29 161.1 173.950432379865 167.708333333333 1.03721996947 0.926125895727569 30 174.1 180.498934777535 170.733333333333 1.05719797800196 0.964548628580987 31 179 189.976007963446 174.5375 1.08845381630564 0.94222424146549 32 190.6 180.746476692351 178.291666666667 1.01376850680449 1.05451571443033 33 190 179.299010937314 181.175 0.989645430866917 1.05968236526652 34 181.6 179.281191825541 184.3125 0.972702295425113 1.01293391766781 35 174.8 181.708864765277 188.8125 0.962377304284817 0.961978383530151 36 180.5 182.28363621351 193.15 0.943741321322859 0.990215050288875 37 196.8 188.347892626237 197.0875 0.955656206640385 1.04487497712829 38 193.8 192.602833130798 200.733333333333 0.95949601360411 1.00621572824107 39 197 202.54693388905 202.858333333333 0.998464941325473 0.972614081178398 40 216.3 208.416943769634 204.075 1.02127621594823 1.03782349020087 41 221.4 213.356147719979 205.7 1.03721996947 1.03770152566955 42 217.9 219.712169778257 207.825 1.05719797800196 0.991752073724062 43 229.7 227.155776238753 208.695833333333 1.08845381630564 1.01120034807555 44 227.4 211.641071937218 208.766666666667 1.01376850680449 1.07446063242137 45 204.2 207.483288103878 209.654166666667 0.989645430866917 0.9841756503192 46 196.6 204.77004489191 210.516666666667 0.972702295425113 0.960101366895618 47 198.8 202.981413095406 210.916666666667 0.962377304284817 0.97940001977698 48 207.5 199.668137803378 211.570833333333 0.943741321322859 1.03922439645495 49 190.7 203.287984656715 212.720833333333 0.955656206640385 0.938078068519536 50 201.6 204.968338006121 213.620833333333 0.95949601360411 0.98356654477034 51 210.5 215.510337043926 215.841666666667 0.998464941325473 0.976751291317853 52 223.5 225.331831096277 220.6375 1.02127621594823 0.99187051786086 53 223.8 235.673664063075 227.216666666667 1.03721996947 0.94961819722081 54 231.2 247.463616700809 234.075 1.05719797800196 0.934278756135404 55 244 262.965906795209 241.595833333333 1.08845381630564 0.927876936495882 56 234.7 254.020819557091 250.570833333333 1.01376850680449 0.923940015661792 57 250.2 257.625323267801 260.320833333333 0.989645430866917 0.971177820667563 58 265.7 263.245664551883 270.633333333333 0.972702295425113 1.00932336512472 59 287.6 271.823469595246 282.45 0.962377304284817 1.05803961824284 60 283.3 279.744588917623 296.420833333333 0.943741321322859 1.01270949009643 61 295.4 297.033876627276 310.816666666667 0.955656206640385 0.994499359312723 62 312.3 310.125103197075 323.216666666667 0.95949601360411 1.00701296599503 63 333.8 331.028570484694 331.5375 0.998464941325473 1.00837217618784 64 347.7 340.523277620104 333.429166666667 1.02127621594823 1.02107557060432 65 383.2 340.527959476747 328.308333333333 1.03721996947 1.12531141521778 66 407.1 337.387114713025 319.133333333333 1.05719797800196 1.20662580829819 67 413.6 335.919523833095 308.620833333333 1.08845381630564 1.23124727994525 68 362.7 NA NA 1.01376850680449 NA 69 321.9 NA NA 0.989645430866917 NA 70 239.4 NA NA 0.972702295425113 NA 71 191 NA NA 0.962377304284817 NA 72 159.7 NA NA 0.943741321322859 NA 73 166.7 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/1zhmh1244016160.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/1zhmh1244016160.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/22aoa1244016160.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/22aoa1244016160.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/3lpsy1244016160.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/3lpsy1244016160.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/48v2x1244016160.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440161998npvp8p2jcw2s0n/48v2x1244016160.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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