Classic decomposition - eigen gegevensreeks - Manuella Loeckx

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 25 May 2008 04:58:48 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2.htm/, Retrieved Sun, 25 May 2008 13:00:03 +0200

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

113000 110000 107000 103000 98000 98000 137000 148000 147000 139000 130000 128000 127000 123000 118000 114000 108000 111000 151000 159000 158000 148000 138000 137000 136000 133000 126000 120000 114000 116000 153000 162000 161000 149000 139000 135000 130000 127000 122000 117000 112000 113000 149000 157000 157000 147000 137000 132000 125000 123000 117000 114000 111000 112000 144000 150000 149000 134000 123000 116000 117000 111000 105000 102000 95000 93000 124000 130000 124000 115000 106000 105000

Text written by user:

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 6 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 113000 NA NA -3408.85416666666 NA 2 110000 NA NA -6502.60416666667 NA 3 107000 NA NA -12294.2708333333 NA 4 103000 NA NA -16763.0208333333 NA 5 98000 NA NA -21638.0208333333 NA 6 98000 NA NA -19690.1041666667 NA 7 137000 138872.395833333 122083.333333333 16789.0625 -1872.39583333334 8 148000 147976.5625 123208.333333333 24768.2291666667 23.4375000000146 9 147000 148486.979166667 124208.333333333 24278.6458333333 -1486.97916666667 10 139000 137914.0625 125125 12789.0625 1085.9375 11 130000 128799.479166667 126000 2799.47916666667 1200.52083333334 12 128000 125830.729166667 126958.333333333 -1127.60416666667 2169.27083333336 13 127000 124674.479166667 128083.333333333 -3408.85416666666 2325.52083333334 14 123000 122622.395833333 129125 -6502.60416666667 377.604166666686 15 118000 117747.395833333 130041.666666667 -12294.2708333333 252.604166666672 16 114000 114111.979166667 130875 -16763.0208333333 -111.979166666657 17 108000 109945.3125 131583.333333333 -21638.0208333333 -1945.31249999999 18 111000 112601.5625 132291.666666667 -19690.1041666667 -1601.56249999999 19 151000 149830.729166667 133041.666666667 16789.0625 1169.27083333334 20 159000 158601.5625 133833.333333333 24768.2291666667 398.437500000029 21 158000 158861.979166667 134583.333333333 24278.6458333333 -861.979166666657 22 148000 147955.729166667 135166.666666667 12789.0625 44.2708333333430 23 138000 138466.145833333 135666.666666667 2799.47916666667 -466.145833333285 24 137000 134997.395833333 136125 -1127.60416666667 2002.60416666669 25 136000 133007.8125 136416.666666667 -3408.85416666666 2992.1875 26 133000 130122.395833333 136625 -6502.60416666667 2877.60416666666 27 126000 124580.729166667 136875 -12294.2708333333 1419.27083333334 28 120000 120278.645833333 137041.666666667 -16763.0208333333 -278.645833333314 29 114000 115486.979166667 137125 -21638.0208333333 -1486.97916666666 30 116000 117393.229166667 137083.333333333 -19690.1041666667 -1393.22916666666 31 153000 153539.0625 136750 16789.0625 -539.0625 32 162000 161018.229166667 136250 24768.2291666667 981.770833333343 33 161000 160111.979166667 135833.333333333 24278.6458333333 888.020833333343 34 149000 148330.729166667 135541.666666667 12789.0625 669.270833333314 35 139000 138132.8125 135333.333333333 2799.47916666667 867.1875 36 135000 133997.395833333 135125 -1127.60416666667 1002.60416666669 37 130000 131424.479166667 134833.333333333 -3408.85416666666 -1424.47916666666 38 127000 127955.729166667 134458.333333333 -6502.60416666667 -955.729166666657 39 122000 121789.0625 134083.333333333 -12294.2708333333 210.937500000029 40 117000 117070.3125 133833.333333333 -16763.0208333333 -70.3124999999709 41 112000 112028.645833333 133666.666666667 -21638.0208333333 -28.6458333333139 42 113000 113768.229166667 133458.333333333 -19690.1041666667 -768.229166666628 43 149000 149914.0625 133125 16789.0625 -914.0625 44 157000 157518.229166667 132750 24768.2291666667 -518.229166666657 45 157000 156653.645833333 132375 24278.6458333333 346.354166666657 46 147000 144830.729166667 132041.666666667 12789.0625 2169.27083333334 47 137000 134674.479166667 131875 2799.47916666667 2325.52083333334 48 132000 130664.0625 131791.666666667 -1127.60416666667 1335.93750000003 49 125000 128132.8125 131541.666666667 -3408.85416666666 -3132.8125 50 123000 124539.0625 131041.666666667 -6502.60416666667 -1539.0625 51 117000 118122.395833333 130416.666666667 -12294.2708333333 -1122.39583333334 52 114000 112778.645833333 129541.666666667 -16763.0208333333 1221.35416666666 53 111000 106778.645833333 128416.666666667 -21638.0208333333 4221.35416666669 54 112000 107476.5625 127166.666666667 -19690.1041666667 4523.43750000001 55 144000 142955.729166667 126166.666666667 16789.0625 1044.27083333334 56 150000 150101.5625 125333.333333333 24768.2291666667 -101.562499999985 57 149000 148611.979166667 124333.333333333 24278.6458333333 388.020833333328 58 134000 136122.395833333 123333.333333333 12789.0625 -2122.39583333333 59 123000 124966.145833333 122166.666666667 2799.47916666667 -1966.14583333333 60 116000 119580.729166667 120708.333333333 -1127.60416666667 -3580.72916666667 61 117000 115674.479166667 119083.333333333 -3408.85416666666 1325.52083333331 62 111000 110914.0625 117416.666666667 -6502.60416666667 85.9375 63 105000 103247.395833333 115541.666666667 -12294.2708333333 1752.60416666666 64 102000 96945.3125 113708.333333333 -16763.0208333333 5054.68750000001 65 95000 90570.3125 112208.333333333 -21638.0208333333 4429.6875 66 93000 91351.5625 111041.666666667 -19690.1041666667 1648.43750000001 67 124000 NA NA 16789.0625 NA 68 130000 NA NA 24768.2291666667 NA 69 124000 NA NA 24278.6458333333 NA 70 115000 NA NA 12789.0625 NA 71 106000 NA NA 2799.47916666667 NA 72 105000 NA NA -1127.60416666667 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/1fleq1211713122.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/1fleq1211713122.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/2t10h1211713122.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/2t10h1211713122.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/3h9a01211713122.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/3h9a01211713122.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/4p9fh1211713122.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713198el2mzrcqazw9eb2/4p9fh1211713122.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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