| classical decomposition van gemiddelde consumptieprijzen van mineraalwater volgens additief model - Rebecca De Cauwer | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Thu, 22 May 2008 10:27:41 -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/22/t12114737140om1yw5p9m4a5sm.htm/, Retrieved Thu, 22 May 2008 18:28:39 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 1,12
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| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 1.12 | NA | NA | -0.00384722222222226 | NA | | 2 | 1.12 | NA | NA | 0.00323611111111115 | NA | | 3 | 1.12 | NA | NA | 0.00606944444444453 | NA | | 4 | 1.13 | NA | NA | 0.00673611111111121 | NA | | 5 | 1.13 | NA | NA | 0.0033194444444445 | NA | | 6 | 1.13 | NA | NA | 0.00190277777777783 | NA | | 7 | 1.14 | 1.13115277777778 | 1.13458333333333 | -0.00343055555555553 | 0.00884722222222245 | | 8 | 1.14 | 1.13123611111111 | 1.13791666666667 | -0.00668055555555555 | 0.00876388888888902 | | 9 | 1.14 | 1.14215277777778 | 1.14208333333333 | 6.94444444443036e-05 | -0.00215277777777745 | | 10 | 1.14 | 1.14506944444444 | 1.14625 | -0.00118055555555567 | -0.00506944444444435 | | 11 | 1.14 | 1.14998611111111 | 1.15041666666667 | -0.000430555555555597 | -0.00998611111111125 | | 12 | 1.15 | 1.14881944444444 | 1.15458333333333 | -0.00576388888888892 | 0.00118055555555552 | | 13 | 1.15 | 1.15448611111111 | 1.15833333333333 | -0.00384722222222226 | -0.00448611111111097 | | 14 | 1.17 | 1.16490277777778 | 1.16166666666667 | 0.00323611111111115 | 0.00509722222222209 | | 15 | 1.17 | 1.17106944444444 | 1.165 | 0.00606944444444453 | -0.00106944444444457 | | 16 | 1.18 | 1.17548611111111 | 1.16875 | 0.00673611111111121 | 0.00451388888888848 | | 17 | 1.18 | 1.17623611111111 | 1.17291666666667 | 0.0033194444444445 | 0.00376388888888868 | | 18 | 1.18 | 1.17856944444444 | 1.17666666666667 | 0.00190277777777783 | 0.00143055555555538 | | 19 | 1.18 | 1.17656944444444 | 1.18 | -0.00343055555555553 | 0.0034305555555556 | | 20 | 1.18 | 1.17581944444444 | 1.1825 | -0.00668055555555555 | 0.00418055555555541 | | 21 | 1.18 | 1.18465277777778 | 1.18458333333333 | 6.94444444443036e-05 | -0.00465277777777784 | | 22 | 1.19 | 1.18590277777778 | 1.18708333333333 | -0.00118055555555567 | 0.00409722222222242 | | 23 | 1.19 | 1.18915277777778 | 1.18958333333333 | -0.000430555555555597 | 0.000847222222222221 | | 24 | 1.19 | 1.18631944444444 | 1.19208333333333 | -0.00576388888888892 | 0.00368055555555569 | | 25 | 1.19 | 1.19073611111111 | 1.19458333333333 | -0.00384722222222226 | -0.000736111111110826 | | 26 | 1.19 | 1.20031944444444 | 1.19708333333333 | 0.00323611111111115 | -0.0103194444444443 | | 27 | 1.2 | 1.20648611111111 | 1.20041666666667 | 0.00606944444444453 | -0.00648611111111097 | | 28 | 1.21 | 1.21131944444444 | 1.20458333333333 | 0.00673611111111121 | -0.00131944444444443 | | 29 | 1.21 | 1.21206944444444 | 1.20875 | 0.0033194444444445 | -0.00206944444444446 | | 30 | 1.21 | 1.21481944444444 | 1.21291666666667 | 0.00190277777777783 | -0.00481944444444449 | | 31 | 1.21 | 1.21490277777778 | 1.21833333333333 | -0.00343055555555553 | -0.0049027777777777 | | 32 | 1.21 | 1.21873611111111 | 1.22541666666667 | -0.00668055555555555 | -0.00873611111111106 | | 33 | 1.23 | 1.23298611111111 | 1.23291666666667 | 6.94444444443036e-05 | -0.00298611111111091 | | 34 | 1.24 | 1.23881944444444 | 1.24 | -0.00118055555555567 | 0.00118055555555552 | | 35 | 1.24 | 1.24665277777778 | 1.24708333333333 | -0.000430555555555597 | -0.00665277777777784 | | 36 | 1.24 | 1.24923611111111 | 1.255 | -0.00576388888888892 | -0.009236111111111 | | 37 | 1.27 | 1.25948611111111 | 1.26333333333333 | -0.00384722222222226 | 0.0105138888888892 | | 38 | 1.28 | 1.27490277777778 | 1.27166666666667 | 0.00323611111111115 | 0.00509722222222231 | | 39 | 1.29 | 1.28565277777778 | 1.27958333333333 | 0.00606944444444453 | 0.00434722222222228 | | 40 | 1.29 | 1.29340277777778 | 1.28666666666667 | 0.00673611111111121 | -0.00340277777777787 | | 41 | 1.3 | 1.29706944444444 | 1.29375 | 0.0033194444444445 | 0.00293055555555566 | | 42 | 1.31 | 1.30315277777778 | 1.30125 | 0.00190277777777783 | 0.00684722222222223 | | 43 | 1.31 | 1.30448611111111 | 1.30791666666667 | -0.00343055555555553 | 0.00551388888888904 | | 44 | 1.31 | 1.30706944444444 | 1.31375 | -0.00668055555555555 | 0.00293055555555588 | | 45 | 1.32 | 1.31965277777778 | 1.31958333333333 | 6.94444444443036e-05 | 0.000347222222222499 | | 46 | 1.32 | 1.32465277777778 | 1.32583333333333 | -0.00118055555555567 | -0.0046527777777774 | | 47 | 1.33 | 1.33165277777778 | 1.33208333333333 | -0.000430555555555597 | -0.00165277777777773 | | 48 | 1.33 | 1.33173611111111 | 1.3375 | -0.00576388888888892 | -0.00173611111111116 | | 49 | 1.34 | 1.33865277777778 | 1.3425 | -0.00384722222222226 | 0.00134722222222217 | | 50 | 1.35 | 1.35073611111111 | 1.3475 | 0.00323611111111115 | -0.00073611111111127 | | 51 | 1.36 | 1.35856944444444 | 1.3525 | 0.00606944444444453 | 0.00143055555555560 | | 52 | 1.37 | 1.36423611111111 | 1.3575 | 0.00673611111111121 | 0.00576388888888912 | | 53 | 1.37 | 1.36581944444444 | 1.3625 | 0.0033194444444445 | 0.00418055555555585 | | 54 | 1.37 | 1.36940277777778 | 1.3675 | 0.00190277777777783 | 0.000597222222222582 | | 55 | 1.37 | 1.36865277777778 | 1.37208333333333 | -0.00343055555555553 | 0.00134722222222239 | | 56 | 1.37 | 1.36998611111111 | 1.37666666666667 | -0.00668055555555555 | 1.38888888892019e-05 | | 57 | 1.38 | 1.38173611111111 | 1.38166666666667 | 6.94444444443036e-05 | -0.00173611111111116 | | 58 | 1.38 | 1.38506944444444 | 1.38625 | -0.00118055555555567 | -0.00506944444444457 | | 59 | 1.39 | 1.38998611111111 | 1.39041666666667 | -0.000430555555555597 | 1.38888888885358e-05 | | 60 | 1.39 | 1.38923611111111 | 1.395 | -0.00576388888888892 | 0.000763888888888786 | | 61 | 1.39 | 1.39615277777778 | 1.4 | -0.00384722222222226 | -0.0061527777777779 | | 62 | 1.41 | 1.40865277777778 | 1.40541666666667 | 0.00323611111111115 | 0.00134722222222217 | | 63 | 1.42 | 1.41773611111111 | 1.41166666666667 | 0.00606944444444453 | 0.00226388888888929 | | 64 | 1.42 | 1.42506944444444 | 1.41833333333333 | 0.00673611111111121 | -0.00506944444444435 | | 65 | 1.42 | 1.42831944444444 | 1.425 | 0.0033194444444445 | -0.0083194444444441 | | 66 | 1.43 | 1.43356944444444 | 1.43166666666667 | 0.00190277777777783 | -0.00356944444444429 | | 67 | 1.43 | 1.43490277777778 | 1.43833333333333 | -0.00343055555555553 | -0.0049027777777777 | | 68 | 1.44 | 1.43790277777778 | 1.44458333333333 | -0.00668055555555555 | 0.00209722222222197 | | 69 | 1.46 | 1.45048611111111 | 1.45041666666667 | 6.94444444443036e-05 | 0.00951388888888904 | | 70 | 1.46 | 1.45506944444444 | 1.45625 | -0.00118055555555567 | 0.00493055555555566 | | 71 | 1.47 | 1.46206944444444 | 1.4625 | -0.000430555555555597 | 0.00793055555555555 | | 72 | 1.47 | 1.46298611111111 | 1.46875 | -0.00576388888888892 | 0.00701388888888888 | | 73 | 1.47 | 1.47115277777778 | 1.475 | -0.00384722222222226 | -0.00115277777777778 | | 74 | 1.48 | 1.48490277777778 | 1.48166666666667 | 0.00323611111111115 | -0.00490277777777792 | | 75 | 1.49 | 1.49398611111111 | 1.48791666666667 | 0.00606944444444453 | -0.00398611111111102 | | 76 | 1.49 | 1.50048611111111 | 1.49375 | 0.00673611111111121 | -0.0104861111111114 | | 77 | 1.5 | 1.50248611111111 | 1.49916666666667 | 0.0033194444444445 | -0.00248611111111119 | | 78 | 1.5 | 1.50648611111111 | 1.50458333333333 | 0.00190277777777783 | -0.00648611111111119 | | 79 | 1.51 | NA | NA | -0.00343055555555553 | NA | | 80 | 1.52 | NA | NA | -0.00668055555555555 | NA | | 81 | 1.53 | NA | NA | 6.94444444443036e-05 | NA | | 82 | 1.53 | NA | NA | -0.00118055555555567 | NA | | 83 | 1.53 | NA | NA | -0.000430555555555597 | NA | | 84 | 1.54 | NA | NA | -0.00576388888888892 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/17m9o1211473659.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/17m9o1211473659.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/2192q1211473659.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/2192q1211473659.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/32re41211473659.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/32re41211473659.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/4i6561211473659.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114737140om1yw5p9m4a5sm/4i6561211473659.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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