| inschrijvingsgeld studenten-additief model-Natalie Van Nylen | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Wed, 21 May 2008 07:15:25 -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/21/t1211375814gh7tngdezfa1oe3.htm/, Retrieved Wed, 21 May 2008 15:16:54 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 513,13
513,13
513,13
513,13
513,13
513,13
513,13
513,13
513,13
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
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545,06
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
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576,3
576,29
576,29
576,29
576,29
576,29
576,29
576,29
576,3
576,29
576,3
576,29
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
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599,12
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| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 513.13 | NA | NA | 2.18614583333334 | NA | | 2 | 513.13 | NA | NA | 1.30885416666666 | NA | | 3 | 513.13 | NA | NA | 0.431562500000003 | NA | | 4 | 513.13 | NA | NA | -0.436840277777776 | NA | | 5 | 513.13 | NA | NA | -1.29642361111109 | NA | | 6 | 513.13 | NA | NA | -2.15434027777775 | NA | | 7 | 513.13 | 514.439826388889 | 517.455416666667 | -3.01559027777777 | -1.30982638888884 | | 8 | 513.13 | 514.817743055556 | 518.69125 | -3.87350694444446 | -1.68774305555553 | | 9 | 513.13 | 515.192326388889 | 519.927083333333 | -4.73475694444445 | -2.06232638888878 | | 10 | 527.96 | 525.885243055556 | 521.162916666667 | 4.72232638888888 | 2.07475694444452 | | 11 | 527.96 | 526.259826388889 | 522.39875 | 3.86107638888889 | 1.70017361111115 | | 12 | 527.96 | 526.636076388889 | 523.634583333333 | 3.00149305555552 | 1.32392361111113 | | 13 | 527.96 | 527.0565625 | 524.870416666667 | 2.18614583333334 | 0.90343750000011 | | 14 | 527.96 | 527.415104166667 | 526.10625 | 1.30885416666666 | 0.544895833333385 | | 15 | 527.96 | 527.773645833333 | 527.342083333333 | 0.431562500000003 | 0.186354166666661 | | 16 | 527.96 | 527.883576388889 | 528.320416666667 | -0.436840277777776 | 0.0764236111110677 | | 17 | 527.96 | 527.744826388889 | 529.04125 | -1.29642361111109 | 0.215173611111140 | | 18 | 527.96 | 527.607743055556 | 529.762083333333 | -2.15434027777775 | 0.352256944444434 | | 19 | 527.96 | 527.467326388889 | 530.482916666667 | -3.01559027777777 | 0.492673611111059 | | 20 | 527.96 | 527.330243055556 | 531.20375 | -3.87350694444446 | 0.629756944444466 | | 21 | 527.96 | 527.189826388889 | 531.924583333333 | -4.73475694444445 | 0.77017361111109 | | 22 | 536.61 | 537.367743055556 | 532.645416666667 | 4.72232638888888 | -0.75774305555558 | | 23 | 536.61 | 537.227326388889 | 533.36625 | 3.86107638888889 | -0.617326388888955 | | 24 | 536.61 | 537.088576388889 | 534.087083333333 | 3.00149305555552 | -0.478576388888882 | | 25 | 536.61 | 536.9940625 | 534.807916666667 | 2.18614583333334 | -0.384062500000027 | | 26 | 536.61 | 536.837604166667 | 535.52875 | 1.30885416666666 | -0.227604166666652 | | 27 | 536.61 | 536.681145833333 | 536.249583333333 | 0.431562500000003 | -0.0711458333332757 | | 28 | 536.61 | 536.525243055555 | 536.962083333333 | -0.436840277777776 | 0.0847569444446208 | | 29 | 536.61 | 536.369826388889 | 537.66625 | -1.29642361111109 | 0.240173611111231 | | 30 | 536.61 | 536.216076388889 | 538.370416666667 | -2.15434027777775 | 0.393923611111290 | | 31 | 536.61 | 536.058993055555 | 539.074583333333 | -3.01559027777777 | 0.551006944444566 | | 32 | 536.61 | 535.905243055555 | 539.77875 | -3.87350694444446 | 0.704756944444625 | | 33 | 536.61 | 535.748159722222 | 540.482916666666 | -4.73475694444445 | 0.861840277778015 | | 34 | 545.06 | 545.909409722222 | 541.187083333333 | 4.72232638888888 | -0.849409722222049 | | 35 | 545.06 | 545.752326388889 | 541.89125 | 3.86107638888889 | -0.692326388888887 | | 36 | 545.06 | 545.596909722222 | 542.595416666667 | 3.00149305555552 | -0.536909722222163 | | 37 | 545.06 | 545.485729166667 | 543.299583333333 | 2.18614583333334 | -0.425729166666656 | | 38 | 545.06 | 545.312604166667 | 544.00375 | 1.30885416666666 | -0.252604166666629 | | 39 | 545.06 | 545.139479166667 | 544.707916666667 | 0.431562500000003 | -0.0794791666667152 | | 40 | 545.06 | 545.422326388889 | 545.859166666667 | -0.436840277777776 | -0.362326388888960 | | 41 | 545.06 | 546.161076388889 | 547.4575 | -1.29642361111109 | -1.10107638888894 | | 42 | 545.06 | 546.901493055556 | 549.055833333333 | -2.15434027777775 | -1.84149305555570 | | 43 | 545.06 | 547.638576388889 | 550.654166666667 | -3.01559027777777 | -2.57857638888902 | | 44 | 545.06 | 548.378993055556 | 552.2525 | -3.87350694444446 | -3.31899305555567 | | 45 | 545.06 | 549.116076388889 | 553.850833333333 | -4.73475694444445 | -4.05607638888887 | | 46 | 564.24 | 560.171493055556 | 555.449166666667 | 4.72232638888888 | 4.06850694444449 | | 47 | 564.24 | 560.908576388889 | 557.0475 | 3.86107638888889 | 3.33142361111118 | | 48 | 564.24 | 561.647326388889 | 558.645833333333 | 3.00149305555552 | 2.59267361111119 | | 49 | 564.24 | 562.4303125 | 560.244166666667 | 2.18614583333334 | 1.80968750000022 | | 50 | 564.24 | 563.151354166667 | 561.8425 | 1.30885416666666 | 1.08864583333354 | | 51 | 564.24 | 563.872395833333 | 563.440833333333 | 0.431562500000003 | 0.367604166666752 | | 52 | 564.24 | 564.196493055555 | 564.633333333333 | -0.436840277777776 | 0.0435069444445162 | | 53 | 564.24 | 564.123576388889 | 565.42 | -1.29642361111109 | 0.116423611111259 | | 54 | 564.24 | 564.052326388889 | 566.206666666666 | -2.15434027777775 | 0.187673611111222 | | 55 | 564.24 | 563.977743055555 | 566.993333333333 | -3.01559027777777 | 0.262256944444516 | | 56 | 564.24 | 563.906493055555 | 567.78 | -3.87350694444446 | 0.333506944444594 | | 57 | 564.24 | 563.831909722222 | 568.566666666666 | -4.73475694444445 | 0.408090277778001 | | 58 | 573.68 | 574.075659722222 | 569.353333333333 | 4.72232638888888 | -0.395659722222149 | | 59 | 573.68 | 574.001076388889 | 570.14 | 3.86107638888889 | -0.321076388888855 | | 60 | 573.68 | 573.928159722222 | 570.926666666667 | 3.00149305555552 | -0.248159722222226 | | 61 | 573.68 | 573.899479166667 | 571.713333333333 | 2.18614583333334 | -0.219479166666702 | | 62 | 573.68 | 573.808854166667 | 572.5 | 1.30885416666666 | -0.128854166666770 | | 63 | 573.68 | 573.718229166667 | 573.286666666667 | 0.431562500000003 | -0.0382291666667243 | | 64 | 573.68 | 573.352326388889 | 573.789166666667 | -0.436840277777776 | 0.327673611111209 | | 65 | 573.68 | 572.710659722222 | 574.007083333333 | -1.29642361111109 | 0.969340277777746 | | 66 | 573.68 | 572.070243055555 | 574.224583333333 | -2.15434027777775 | 1.60975694444448 | | 67 | 573.68 | 571.426493055556 | 574.442083333333 | -3.01559027777777 | 2.25350694444444 | | 68 | 573.68 | 570.786076388889 | 574.659583333333 | -3.87350694444446 | 2.89392361111106 | | 69 | 573.68 | 570.142326388889 | 574.877083333333 | -4.73475694444445 | 3.53767361111113 | | 70 | 576.3 | 579.816909722222 | 575.094583333333 | 4.72232638888888 | -3.51690972222218 | | 71 | 576.29 | 579.173159722222 | 575.312083333333 | 3.86107638888889 | -2.88315972222222 | | 72 | 576.29 | 578.531493055555 | 575.53 | 3.00149305555552 | -2.24149305555545 | | 73 | 576.29 | 577.9340625 | 575.747916666666 | 2.18614583333334 | -1.64406249999979 | | 74 | 576.29 | 577.2746875 | 575.965833333333 | 1.30885416666666 | -0.984687499999723 | | 75 | 576.29 | 576.6153125 | 576.18375 | 0.431562500000003 | -0.325312499999882 | | 76 | 576.29 | 576.420243055555 | 576.857083333333 | -0.436840277777776 | -0.130243055555525 | | 77 | 576.29 | 576.690243055555 | 577.986666666666 | -1.29642361111109 | -0.400243055555393 | | 78 | 576.3 | 576.962326388889 | 579.116666666666 | -2.15434027777775 | -0.6623263888888 | | 79 | 576.29 | 577.231076388889 | 580.246666666666 | -3.01559027777777 | -0.941076388888746 | | 80 | 576.3 | 577.503159722222 | 581.376666666667 | -3.87350694444446 | -1.20315972222215 | | 81 | 576.29 | 577.771909722222 | 582.506666666667 | -4.73475694444445 | -1.4819097222221 | | 82 | 589.85 | 588.358993055555 | 583.636666666667 | 4.72232638888888 | 1.49100694444462 | | 83 | 589.85 | 588.627743055555 | 584.766666666667 | 3.86107638888889 | 1.22225694444455 | | 84 | 589.85 | 588.897743055556 | 585.89625 | 3.00149305555552 | 0.952256944444343 | | 85 | 589.85 | 589.211979166667 | 587.025833333333 | 2.18614583333334 | 0.638020833333258 | | 86 | 589.85 | 589.464270833334 | 588.155416666667 | 1.30885416666666 | 0.385729166666465 | | 87 | 589.85 | 589.7165625 | 589.285 | 0.431562500000003 | 0.1334374999999 | | 88 | 589.85 | 589.799409722222 | 590.23625 | -0.436840277777776 | 0.050590277777701 | | 89 | 589.85 | 589.712326388889 | 591.00875 | -1.29642361111109 | 0.137673611110927 | | 90 | 589.85 | 589.626909722222 | 591.78125 | -2.15434027777775 | 0.223090277777715 | | 91 | 589.85 | NA | NA | -3.01559027777777 | NA | | 92 | 589.85 | NA | NA | -3.87350694444446 | NA | | 93 | 589.85 | NA | NA | -4.73475694444445 | NA | | 94 | 599.12 | NA | NA | 4.72232638888888 | NA | | 95 | 599.12 | NA | NA | 3.86107638888889 | NA | | 96 | 599.12 | NA | NA | 3.00149305555552 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/14r4w1211375720.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/14r4w1211375720.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/2sym71211375720.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/2sym71211375720.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/39aj11211375720.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/39aj11211375720.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/4gshu1211375720.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211375814gh7tngdezfa1oe3/4gshu1211375720.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')
| | |
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