decompositie wisselkoers dollar/euro

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 20 May 2010 11:57:43 +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/20/t1274356722lwc7yqrllxxfls4.htm/, Retrieved Thu, 20 May 2010 13:58:42 +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/20/t1274356722lwc7yqrllxxfls4.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 «

1,1591 1,1203 1,0886 1,0701 1,0630 1,0377 1,0370 1,0605 1,0497 1,0706 1,0328 1,0110 1,0131 0,9834 0,9643 0,9449 0,9059 0,9505 0,9386 0,9045 0,8695 0,8525 0,8552 0,8983 0,9376 0,9205 0,9083 0,8925 0,8753 0,8530 0,8615 0,9014 0,9114 0,9050 0,8883 0,8912 0,8832 0,8707 0,8766 0,8860 0,9170 0,9561 0,9935 0,9781 0,9806 0,9812 1,0013 1,0194 1,0622 1,0785 1,0797 1,0862 1,1556 1,1674 1,1365 1,1155 1,1267 1,1714 1,1710 1,2298 1,2638 1,2640 1,2261 1,1989 1,2000 1,2146 1,2266 1,2191 1,2224 1,2507 1,2997 1,3406 1,3123 1,3013 1,3185 1,2943 1,2697 1,2155 1,2041 1,2295 1,2234 1,2022 1,1789 1,1861 1,2126 1,1940 1,2028 1,2273 1,2767 1,2661 1,2681 1,2810 1,2722 1,2617 1,2888 1,3205 1,2993 1,3080 1,3246 1,3513 1,3518 1,3421 1,3726 1,3626 1,3910 1,4233 1,4683 1,4559 1,4728 1,4759 1,5520 1,5754 1,5554 1,5562 1,5759 1,4955 1,4342 1,3266 1,2744 1,3511 1,3244 1,2797 1,3050 1,3199 1,3646 1,4014 1,4092 1,4266 etc...

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 1.1591 NA NA 0.0109630902777778 NA 2 1.1203 NA NA -0.00264315972222224 NA 3 1.0886 NA NA 0.00232225694444445 NA 4 1.0701 NA NA 0.000788506944444475 NA 5 1.063 NA NA 0.00669559027777774 NA 6 1.0377 NA NA 0.00801517361111106 NA 7 1.037 1.06788684027778 1.06061666666667 0.0072701736111112 -0.030886840277778 8 1.0605 1.04807642361111 1.04882916666667 -0.000752743055555508 0.0124235763888891 9 1.0497 1.02896725694444 1.03794583333333 -0.00897857638888894 0.0207327430555557 10 1.0706 1.01303892361111 1.02755 -0.0145110763888889 0.057561076388889 11 1.0328 1.00032892361111 1.0157875 -0.0154585763888889 0.0324710763888887 12 1.011 1.01189767361111 1.00560833333333 0.00628934027777775 -0.000897673611111038 13 1.0131 1.00883809027778 0.997875 0.0109630902777778 0.0042619097222224 14 0.9834 0.984631840277778 0.987275 -0.00264315972222224 -0.00123184027777756 15 0.9643 0.97558892361111 0.973266666666667 0.00232225694444445 -0.0112889236111109 16 0.9449 0.957459340277778 0.956670833333333 0.000788506944444475 -0.0125593402777777 17 0.9059 0.946878923611111 0.940183333333333 0.00669559027777774 -0.040978923611111 18 0.9505 0.936102673611111 0.9280875 0.00801517361111106 0.0143973263888890 19 0.9386 0.927516006944444 0.920245833333333 0.0072701736111112 0.0110839930555556 20 0.9045 0.913726423611111 0.914479166666667 -0.000752743055555508 -0.00922642361111103 21 0.8695 0.900546423611111 0.909525 -0.00897857638888894 -0.0310464236111109 22 0.8525 0.890497256944444 0.905008333333333 -0.0145110763888889 -0.0379972569444443 23 0.8552 0.886091423611111 0.90155 -0.0154585763888889 -0.0308914236111110 24 0.8983 0.902501840277778 0.8962125 0.00628934027777775 -0.00420184027777759 25 0.9376 0.899900590277778 0.8889375 0.0109630902777778 0.0376994097222224 26 0.9205 0.882952673611111 0.885595833333333 -0.00264315972222224 0.037547326388889 27 0.9083 0.889534756944445 0.8872125 0.00232225694444445 0.0187652430555555 28 0.8925 0.891934340277778 0.891145833333333 0.000788506944444475 0.000565659722222112 29 0.8753 0.901408090277778 0.8947125 0.00669559027777774 -0.0261080902777778 30 0.853 0.903811006944444 0.895795833333333 0.00801517361111106 -0.0508110069444444 31 0.8615 0.900503506944444 0.893233333333333 0.0072701736111112 -0.0390035069444443 32 0.9014 0.888138923611111 0.888891666666667 -0.000752743055555508 0.0132610763888888 33 0.9114 0.876517256944444 0.885495833333333 -0.00897857638888894 0.0348827430555555 34 0.905 0.869393090277778 0.883904166666667 -0.0145110763888889 0.0356069097222221 35 0.8883 0.869912256944444 0.885370833333333 -0.0154585763888889 0.0183877430555556 36 0.8912 0.897693506944444 0.891404166666667 0.00628934027777775 -0.0064935069444444 37 0.8832 0.912163090277778 0.9012 0.0109630902777778 -0.0289630902777779 38 0.8707 0.907252673611111 0.909895833333333 -0.00264315972222224 -0.036552673611111 39 0.8766 0.918297256944444 0.915975 0.00232225694444445 -0.0416972569444444 40 0.886 0.922821840277778 0.922033333333333 0.000788506944444475 -0.0368218402777777 41 0.917 0.936612256944444 0.929916666666667 0.00669559027777774 -0.0196122569444442 42 0.9561 0.947981840277778 0.939966666666667 0.00801517361111106 0.0081181597222223 43 0.9935 0.960036840277778 0.952766666666667 0.0072701736111112 0.0334631597222224 44 0.9781 0.968130590277778 0.968883333333333 -0.000752743055555508 0.00996940972222216 45 0.9806 0.977025590277778 0.986004166666667 -0.00897857638888894 0.00357440972222234 46 0.9812 0.988297256944444 1.00280833333333 -0.0145110763888889 -0.00709725694444419 47 1.0013 1.00563309027778 1.02109166666667 -0.0154585763888889 -0.00433309027777784 48 1.0194 1.04612684027778 1.0398375 0.00628934027777775 -0.0267268402777776 49 1.0622 1.06556309027778 1.0546 0.0109630902777778 -0.0033630902777777 50 1.0785 1.06364017361111 1.06628333333333 -0.00264315972222224 0.0148598263888888 51 1.0797 1.08041809027778 1.07809583333333 0.00232225694444445 -0.000718090277777694 52 1.0862 1.09289684027778 1.09210833333333 0.000788506944444475 -0.00669684027777784 53 1.1556 1.11379975694444 1.10710416666667 0.00669559027777774 0.0418002430555553 54 1.1674 1.13095684027778 1.12294166666667 0.00801517361111106 0.0364431597222219 55 1.1365 1.14737850694444 1.14010833333333 0.0072701736111112 -0.0108785069444444 56 1.1155 1.15548475694444 1.1562375 -0.000752743055555508 -0.0399847569444445 57 1.1267 1.16108809027778 1.17006666666667 -0.00897857638888894 -0.0343880902777778 58 1.1714 1.16635142361111 1.1808625 -0.0145110763888889 0.00504857638888878 59 1.171 1.17194975694444 1.18740833333333 -0.0154585763888889 -0.000949756944444546 60 1.2298 1.19751434027778 1.191225 0.00628934027777775 0.0322856597222221 61 1.2638 1.20790892361111 1.19694583333333 0.0109630902777778 0.0558910763888891 62 1.264 1.20237350694444 1.20501666666667 -0.00264315972222224 0.0616264930555557 63 1.2261 1.21564309027778 1.21332083333333 0.00232225694444445 0.0104569097222222 64 1.1989 1.22140100694444 1.2206125 0.000788506944444475 -0.0225010069444442 65 1.2 1.23597475694444 1.22927916666667 0.00669559027777774 -0.0359747569444442 66 1.2146 1.24727350694444 1.23925833333333 0.00801517361111106 -0.0326735069444446 67 1.2266 1.25316600694444 1.24589583333333 0.0072701736111112 -0.0265660069444442 68 1.2191 1.24871809027778 1.24947083333333 -0.000752743055555508 -0.0296180902777774 69 1.2224 1.24589642361111 1.254875 -0.00897857638888894 -0.0234964236111110 70 1.2507 1.24818892361111 1.2627 -0.0145110763888889 0.0025110763888887 71 1.2997 1.25412059027778 1.26957916666667 -0.0154585763888889 0.0455794097222222 72 1.3406 1.27881017361111 1.27252083333333 0.00628934027777775 0.0617898263888887 73 1.3123 1.28258392361111 1.27162083333333 0.0109630902777778 0.0297160763888891 74 1.3013 1.26847350694444 1.27111666666667 -0.00264315972222224 0.0328264930555557 75 1.3185 1.27391392361111 1.27159166666667 0.00232225694444445 0.044586076388889 76 1.2943 1.27040100694444 1.2696125 0.000788506944444475 0.0238989930555558 77 1.2697 1.26925392361111 1.26255833333333 0.00669559027777774 0.000446076388888939 78 1.2155 1.25910267361111 1.2510875 0.00801517361111106 -0.043602673611111 79 1.2041 1.24776600694444 1.24049583333333 0.0072701736111112 -0.0436660069444446 80 1.2295 1.23111809027778 1.23187083333333 -0.000752743055555508 -0.00161809027777760 81 1.2234 1.21360059027778 1.22257916666667 -0.00897857638888894 0.00979940972222226 82 1.2022 1.20045559027778 1.21496666666667 -0.0145110763888889 0.00174440972222256 83 1.1789 1.19700809027778 1.21246666666667 -0.0154585763888889 -0.0181080902777777 84 1.1861 1.22115600694444 1.21486666666667 0.00628934027777775 -0.0350560069444443 85 1.2126 1.23060475694444 1.21964166666667 0.0109630902777778 -0.0180047569444444 86 1.194 1.22181100694444 1.22445416666667 -0.00264315972222224 -0.0278110069444444 87 1.2028 1.23095559027778 1.22863333333333 0.00232225694444445 -0.0281555902777779 88 1.2273 1.23393434027778 1.23314583333333 0.000788506944444475 -0.00663434027777754 89 1.2767 1.24689975694444 1.24020416666667 0.00669559027777774 0.0298002430555557 90 1.2661 1.25839850694444 1.25038333333333 0.00801517361111106 0.00770149305555567 91 1.2681 1.26686600694444 1.25959583333333 0.0072701736111112 0.00123399305555560 92 1.281 1.26720559027778 1.26795833333333 -0.000752743055555508 0.0137944097222222 93 1.2722 1.26880475694444 1.27778333333333 -0.00897857638888894 0.00339524305555594 94 1.2617 1.27351392361111 1.288025 -0.0145110763888889 -0.011813923611111 95 1.2888 1.28086225694444 1.29632083333333 -0.0154585763888889 0.00793774305555561 96 1.3205 1.30890600694444 1.30261666666667 0.00628934027777775 0.0115939930555558 97 1.2993 1.32110059027778 1.3101375 0.0109630902777778 -0.0218005902777778 98 1.308 1.31524850694444 1.31789166666667 -0.00264315972222224 -0.00724850694444434 99 1.3246 1.32856392361111 1.32624166666667 0.00232225694444445 -0.00396392361111109 100 1.3513 1.33871350694444 1.337925 0.000788506944444475 0.0125864930555559 101 1.3518 1.35883309027778 1.3521375 0.00669559027777774 -0.00703309027777754 102 1.3421 1.37327350694444 1.36525833333333 0.00801517361111106 -0.0311735069444441 103 1.3726 1.38539934027778 1.37812916666667 0.0072701736111112 -0.0127993402777775 104 1.3626 1.39160142361111 1.39235416666667 -0.000752743055555508 -0.0290014236111109 105 1.391 1.39984642361111 1.408825 -0.00897857638888894 -0.00884642361111099 106 1.4233 1.41312642361111 1.4276375 -0.0145110763888889 0.0101735763888893 107 1.4683 1.42999975694444 1.44545833333333 -0.0154585763888889 0.0383002430555557 108 1.4559 1.46915184027778 1.4628625 0.00628934027777775 -0.0132518402777777 109 1.4728 1.49121725694444 1.48025416666667 0.0109630902777778 -0.0184172569444445 110 1.4759 1.49161934027778 1.4942625 -0.00264315972222224 -0.0157193402777775 111 1.552 1.50392225694444 1.5016 0.00232225694444445 0.0480777430555555 112 1.5754 1.50015934027778 1.49937083333333 0.000788506944444475 0.0752406597222222 113 1.5554 1.49395809027778 1.4872625 0.00669559027777774 0.0614419097222223 114 1.5562 1.48283184027778 1.47481666666667 0.00801517361111106 0.073368159722222 115 1.5759 1.47153684027778 1.46426666666667 0.0072701736111112 0.104363159722223 116 1.4955 1.44915559027778 1.44990833333333 -0.000752743055555508 0.0463444097222225 117 1.4342 1.42246309027778 1.43144166666667 -0.00897857638888894 0.0117369097222222 118 1.3266 1.39599309027778 1.41050416666667 -0.0145110763888889 -0.0693930902777777 119 1.2744 1.37644975694444 1.39190833333333 -0.0154585763888889 -0.102049756944445 120 1.3511 1.38379767361111 1.37750833333333 0.00628934027777775 -0.0326976736111109 121 1.3244 1.37507559027778 1.3641125 0.0109630902777778 -0.0506755902777776 122 1.2797 1.35165267361111 1.35429583333333 -0.00264315972222224 -0.0719526736111111 123 1.305 1.35471809027778 1.35239583333333 0.00232225694444445 -0.0497180902777781 124 1.3199 1.36063434027778 1.35984583333333 0.000788506944444475 -0.0407343402777778 125 1.3646 1.38203725694444 1.37534166666667 0.00669559027777774 -0.0174372569444443 126 1.4014 1.39682350694444 1.38880833333333 0.00801517361111106 0.00457649305555541 127 1.4092 NA NA 0.0072701736111112 NA 128 1.4266 NA NA -0.000752743055555508 NA 129 1.4575 NA NA -0.00897857638888894 NA 130 1.4821 NA NA -0.0145110763888889 NA 131 1.4908 NA NA -0.0154585763888889 NA 132 1.4579 NA NA 0.00628934027777775 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/13ipd1274356659.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/13ipd1274356659.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/23ipd1274356659.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/23ipd1274356659.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/3v9og1274356659.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/3v9og1274356659.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/4v9og1274356659.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/20/t1274356722lwc7yqrllxxfls4/4v9og1274356659.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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