opgave 9 - verbetering - manuella loeckx

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 28 May 2008 05:23:41 -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/28/t1211973862b6zgjgldp96sabt.htm/, Retrieved Wed, 28 May 2008 13:24:22 +0200

User-defined keywords:

Dataseries X:

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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 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 113000 NA NA 0.974067596083232 NA 2 110000 NA NA 0.950678958898946 NA 3 107000 NA NA 0.907193013285526 NA 4 103000 NA NA 0.873749438185297 NA 5 98000 NA NA 0.837175825540257 NA 6 98000 NA NA 0.851722529400722 NA 7 137000 137549.124009685 122083.333333333 1.12668224444793 0.996007797115116 8 148000 146261.427401721 123208.333333333 1.18710661401464 1.01188674710185 9 147000 147050.735626423 124208.333333333 1.18390394331907 0.999654978764937 10 139000 137216.257502888 125125 1.09663342659650 1.0129994982342 11 130000 128615.082165021 126000 1.02075462035731 1.01076792714872 12 128000 125730.873488984 126958.333333333 0.990331789870567 1.01804748864021 13 127000 124761.824598327 128083.333333333 0.974067596083232 1.01793958535697 14 123000 122756.420567826 129125 0.950678958898946 1.00198425003798 15 118000 117972.891436005 130041.666666667 0.907193013285526 1.00022978638283 16 114000 114351.957722501 130875 0.873749438185297 0.99692215394025 17 108000 110158.385710672 131583.333333333 0.837175825540257 0.980406523781665 18 111000 112675.792951970 132291.666666667 0.851722529400722 0.98512730278557 19 151000 149895.683605093 133041.666666667 1.12668224444793 1.00736723278714 20 159000 158874.435175626 133833.333333333 1.18710661401464 1.00079034002063 21 158000 159333.739038358 134583.333333333 1.18390394331907 0.991629274211427 22 148000 148228.284828294 135166.666666667 1.09663342659650 0.998459910478229 23 138000 138482.376828475 135666.666666667 1.02075462035731 0.996516691585442 24 137000 134808.914896131 136125 0.990331789870567 1.01625326563571 25 136000 132879.054565688 136416.666666667 0.974067596083232 1.02348711348461 26 133000 129886.512759569 136625 0.950678958898946 1.02397082787337 27 126000 124172.043693456 136875 0.907193013285526 1.01472115825891 28 120000 119740.079257977 137041.666666667 0.873749438185297 1.00217070795037 29 114000 114797.735077208 137125 0.837175825540257 0.993050951077813 30 116000 116756.963405349 137083.333333333 0.851722529400722 0.993516760086326 31 153000 154073.796928254 136750 1.12668224444793 0.99303063240043 32 162000 161743.276159495 136250 1.18710661401464 1.00158723037273 33 161000 160813.618967507 135833.333333333 1.18390394331907 1.00115898786241 34 149000 148639.522363268 135541.666666667 1.09663342659650 1.00242518026835 35 139000 138142.125288356 135333.333333333 1.02075462035731 1.00621008768943 36 135000 133818.583106260 135125 0.990331789870567 1.00882849650860 37 130000 131336.780871889 134833.333333333 0.974067596083232 0.989821732624975 38 127000 127826.708348621 134458.333333333 0.950678958898946 0.993532585174875 39 122000 121639.463198034 134083.333333333 0.907193013285526 1.00296397889704 40 117000 116936.799810466 133833.333333333 0.873749438185297 1.00054046450422 41 112000 111902.502013881 133666.666666667 0.837175825540257 1.00087127619458 42 113000 113669.469236271 133458.333333333 0.851722529400722 0.994110386537657 43 149000 149989.573792131 133125 1.12668224444793 0.993402382798273 44 157000 157588.403010444 132750 1.18710661401464 0.996266203608875 45 157000 156719.284496862 132375 1.18390394331907 1.00179119949430 46 147000 144801.30537018 132041.666666667 1.09663342659650 1.01518421829278 47 137000 134612.01555962 131875 1.02075462035731 1.01773975696339 48 132000 130517.477140025 131791.666666667 0.990331789870567 1.01135880720698 49 125000 128130.475034782 131541.666666667 0.974067596083232 0.97556806814357 50 123000 124578.555239049 131041.666666667 0.950678958898946 0.987328836523908 51 117000 118313.088815987 130416.666666667 0.907193013285526 0.988901576071354 52 114000 113186.958471587 129541.666666667 0.873749438185297 1.00718317321529 53 111000 107507.328929795 128416.666666667 0.837175825540257 1.03248774855606 54 112000 108310.714988792 127166.666666667 0.851722529400722 1.03406205020057 55 144000 142149.743174514 126166.666666667 1.12668224444793 1.01301625162428 56 150000 148784.028956502 125333.333333333 1.18710661401464 1.00817272560789 57 149000 147198.723619338 124333.333333333 1.18390394331907 1.01223703804199 58 134000 135251.455946902 123333.333333333 1.09663342659650 0.990747190570773 59 123000 124702.189453651 122166.666666667 1.02075462035731 0.986349963371865 60 116000 119541.299802293 120708.333333333 0.990331789870567 0.970375930258832 61 117000 115995.216233578 119083.333333333 0.974067596083232 1.00866228624807 62 111000 111625.554424051 117416.666666667 0.950678958898946 0.994395956846271 63 105000 104818.592743365 115541.666666667 0.907193013285526 1.00173067823071 64 102000 99352.5923669865 113708.333333333 0.873749438185297 1.02664658837723 65 95000 93938.1040908297 112208.333333333 0.837175825540257 1.01130420844074 66 93000 94576.6892022051 111041.666666667 0.851722529400722 0.983328987137262 67 124000 NA NA 1.12668224444793 NA 68 130000 NA NA 1.18710661401464 NA 69 124000 NA NA 1.18390394331907 NA 70 115000 NA NA 1.09663342659650 NA 71 106000 NA NA 1.02075462035731 NA 72 105000 NA NA 0.990331789870567 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/19dim1211973815.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/19dim1211973815.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/2jb6r1211973815.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/2jb6r1211973815.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/3d2nj1211973815.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/3d2nj1211973815.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/4nvib1211973815.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t1211973862b6zgjgldp96sabt/4nvib1211973815.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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