Ruts Wouter:decompositie additiefmodel eigen reeks

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 01 Jun 2008 09:21:43 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l.htm/, Retrieved Sun, 01 Jun 2008 15:26:04 +0000

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

6.5300 6.5400 6.5400 6.5100 6.5100 6.4900 6.4600 6.4600 6.5200 6.4800 6.4900 6.4800 6.5300 6.4900 6.4800 6.5700 6.5300 6.5700 6.5500 6.5700 6.6200 6.5600 6.6500 6.5900 6.6800 6.7500 6.7700 6.8200 6.8800 6.8100 6.8700 6.9100 6.9800 7.0400 6.9900 7.0800 7.1300 7.1000 7.0200 7.0300 7.1200 7.1100 7.0900 7.0200 7.0300 7.0600 7.0500 7.1100 7.0600 7.0500 7.1100 7.0900 7.1300 7.0300 7.0600 7.1100 7.0800 7.1300 7.0000 7.0200 6.9600 6.9800 7.0200 7.0200 7.0600 7.0200 6.9400 6.9700 6.9700 6.9400 6.9300 7.0000 6.9700 6.9700 6.9800 6.9200 7.0000 6.9400 6.9700 6.9300 6.9200 6.8400 6.8600 6.8600 6.8400

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 6.53 NA NA 0.000993055555555333 NA 2 6.54 NA NA -0.00525694444444431 NA 3 6.54 NA NA -0.00725694444444445 NA 4 6.51 NA NA 0.0111597222222222 NA 5 6.51 NA NA 0.041659722222222 NA 6 6.49 NA NA -0.00234027777777781 NA 7 6.46 6.48449305555556 6.50083333333333 -0.0163402777777780 -0.0244930555555554 8 6.46 6.48874305555556 6.49875 -0.0100069444444446 -0.0287430555555561 9 6.52 6.49599305555556 6.49416666666667 0.00182638888888915 0.0240069444444444 10 6.48 6.49890972222222 6.49416666666667 0.00474305555555583 -0.0189097222222223 11 6.49 6.47340972222222 6.4975 -0.0240902777777777 0.0165902777777784 12 6.48 6.50657638888889 6.50166666666667 0.00490972222222252 -0.0265763888888886 13 6.53 6.50974305555556 6.50875 0.000993055555555333 0.0202569444444451 14 6.49 6.51182638888889 6.51708333333333 -0.00525694444444431 -0.021826388888889 15 6.48 6.51857638888889 6.52583333333333 -0.00725694444444445 -0.0385763888888881 16 6.57 6.54449305555556 6.53333333333333 0.0111597222222222 0.0255069444444445 17 6.53 6.58499305555556 6.54333333333333 0.041659722222222 -0.0549930555555553 18 6.57 6.55224305555556 6.55458333333333 -0.00234027777777781 0.0177569444444448 19 6.55 6.54907638888889 6.56541666666667 -0.0163402777777780 0.00092361111111039 20 6.57 6.57249305555556 6.5825 -0.0100069444444446 -0.00249305555555512 21 6.62 6.60724305555556 6.60541666666667 0.00182638888888915 0.0127569444444440 22 6.56 6.63265972222222 6.62791666666667 0.00474305555555583 -0.0726597222222232 23 6.65 6.62882638888889 6.65291666666667 -0.0240902777777777 0.0211736111111112 24 6.59 6.68240972222222 6.6775 0.00490972222222252 -0.0924097222222224 25 6.68 6.70182638888889 6.70083333333333 0.000993055555555333 -0.0218263888888881 26 6.75 6.72307638888889 6.72833333333333 -0.00525694444444431 0.0269236111111120 27 6.77 6.75024305555556 6.7575 -0.00725694444444445 0.0197569444444436 28 6.82 6.80365972222222 6.7925 0.0111597222222222 0.0163402777777772 29 6.88 6.86832638888889 6.82666666666667 0.041659722222222 0.0116736111111120 30 6.81 6.85890972222222 6.86125 -0.00234027777777781 -0.0489097222222226 31 6.87 6.88407638888889 6.90041666666667 -0.0163402777777780 -0.0140763888888884 32 6.91 6.92374305555555 6.93375 -0.0100069444444446 -0.0137430555555547 33 6.98 6.96057638888889 6.95875 0.00182638888888915 0.0194236111111117 34 7.04 6.98265972222222 6.97791666666667 0.00474305555555583 0.0573402777777776 35 6.99 6.97257638888889 6.99666666666667 -0.0240902777777777 0.0174236111111119 36 7.08 7.02407638888889 7.01916666666667 0.00490972222222252 0.0559236111111101 37 7.13 7.04182638888889 7.04083333333333 0.000993055555555333 0.0881736111111113 38 7.1 7.04932638888889 7.05458333333333 -0.00525694444444431 0.0506736111111108 39 7.02 7.05399305555556 7.06125 -0.00725694444444445 -0.0339930555555563 40 7.03 7.07532638888889 7.06416666666667 0.0111597222222222 -0.0453263888888866 41 7.12 7.10915972222222 7.0675 0.041659722222222 0.0108402777777794 42 7.11 7.06890972222222 7.07125 -0.00234027777777781 0.0410902777777782 43 7.09 7.05324305555555 7.06958333333333 -0.0163402777777780 0.0367569444444449 44 7.02 7.05457638888889 7.06458333333333 -0.0100069444444446 -0.0345763888888886 45 7.03 7.06807638888889 7.06625 0.00182638888888915 -0.0380763888888893 46 7.06 7.07724305555556 7.0725 0.00474305555555583 -0.0172430555555563 47 7.05 7.05132638888889 7.07541666666667 -0.0240902777777777 -0.00132638888888970 48 7.11 7.07740972222222 7.0725 0.00490972222222252 0.0325902777777793 49 7.06 7.06890972222222 7.06791666666667 0.000993055555555333 -0.00890972222222253 50 7.05 7.06515972222222 7.07041666666667 -0.00525694444444431 -0.0151597222222222 51 7.11 7.06899305555555 7.07625 -0.00725694444444445 0.0410069444444465 52 7.09 7.09240972222222 7.08125 0.0111597222222222 -0.00240972222222258 53 7.13 7.12374305555555 7.08208333333333 0.041659722222222 0.00625694444444491 54 7.03 7.07390972222222 7.07625 -0.00234027777777781 -0.0439097222222209 55 7.06 7.05199305555555 7.06833333333333 -0.0163402777777780 0.00800694444444527 56 7.11 7.05124305555555 7.06125 -0.0100069444444446 0.0587569444444451 57 7.08 7.05640972222222 7.05458333333333 0.00182638888888915 0.023590277777779 58 7.13 7.05265972222222 7.04791666666667 0.00474305555555583 0.077340277777778 59 7 7.01799305555555 7.04208333333333 -0.0240902777777777 -0.0179930555555545 60 7.02 7.04365972222222 7.03875 0.00490972222222252 -0.0236597222222228 61 6.96 7.03432638888889 7.03333333333333 0.000993055555555333 -0.0743263888888874 62 6.98 7.01724305555555 7.0225 -0.00525694444444431 -0.0372430555555532 63 7.02 7.00482638888889 7.01208333333333 -0.00725694444444445 0.0151736111111109 64 7.02 7.01074305555556 6.99958333333333 0.0111597222222222 0.00925694444444325 65 7.06 7.03040972222222 6.98875 0.041659722222222 0.0295902777777775 66 7.02 6.98265972222222 6.985 -0.00234027777777781 0.0373402777777780 67 6.94 6.96824305555556 6.98458333333333 -0.0163402777777780 -0.0282430555555546 68 6.97 6.97457638888889 6.98458333333333 -0.0100069444444446 -0.00457638888888923 69 6.97 6.98432638888889 6.9825 0.00182638888888915 -0.0143263888888896 70 6.94 6.98140972222222 6.97666666666666 0.00474305555555583 -0.0414097222222205 71 6.93 6.94590972222222 6.97 -0.0240902777777777 -0.0159097222222213 72 7 6.96907638888889 6.96416666666667 0.00490972222222252 0.0309236111111115 73 6.97 6.96307638888889 6.96208333333333 0.000993055555555333 0.0069236111111115 74 6.97 6.95640972222222 6.96166666666667 -0.00525694444444431 0.0135902777777783 75 6.98 6.95065972222222 6.95791666666667 -0.00725694444444445 0.0293402777777789 76 6.92 6.96282638888889 6.95166666666667 0.0111597222222222 -0.042826388888888 77 7 6.98624305555555 6.94458333333333 0.041659722222222 0.0137569444444452 78 6.94 6.93349305555556 6.93583333333333 -0.00234027777777781 0.00650694444444433 79 6.97 6.90824305555555 6.92458333333333 -0.0163402777777780 0.0617569444444452 80 6.93 NA NA -0.0100069444444446 NA 81 6.92 NA NA 0.00182638888888915 NA 82 6.84 NA NA 0.00474305555555583 NA 83 6.86 NA NA -0.0240902777777777 NA 84 6.86 NA NA 0.00490972222222252 NA 85 6.84 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/15sab1212333698.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/15sab1212333698.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/273ln1212333698.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/273ln1212333698.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/3pnue1212333698.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/3pnue1212333698.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/423ke1212333698.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jun/01/t1212333964sjxk9h6r6bx6n5l/423ke1212333698.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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