| verkoopprijzen scrabble - Cynthia D'Hooghe | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Mon, 19 May 2008 07:52:38 -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/19/t1211205201a3m4zut0d1unjdz.htm/, Retrieved Mon, 19 May 2008 15:53:26 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 24,65
25,24
25,56
25,9
25,87
25,78
25,78
25,74
25,78
25,73
24,67
24,31
24,56
25
25,38
25,99
26,22
26,19
26,22
26,22
26,61
26,72
25,46
25,48
25,59
25,88
26
26,97
27,2
27,19
27,19
27,19
27,26
26,9
26,11
25,87
26,02
26,31
26,37
26,52
26,86
26,92
26,98
26,98
27,03
26,75
26,39
26,3
26,3
26,52
26,53
26,98
27,22
27,34
27,41
27,47
27,46
27,53
27,21
26,91
26,95
26,91
27,39
27,62
27,79
27,88
27,9
28,09
28,46
28,73
27,93
27,61
| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 24.65 | NA | NA | -0.691753472222224 | NA | | 2 | 25.24 | NA | NA | -0.416753472222225 | NA | | 3 | 25.56 | NA | NA | -0.309774305555555 | NA | | 4 | 25.9 | NA | NA | 0.198975694444447 | NA | | 5 | 25.87 | NA | NA | 0.413767361111111 | NA | | 6 | 25.78 | NA | NA | 0.395225694444447 | NA | | 7 | 25.78 | 25.7969965277778 | 25.41375 | 0.38324652777778 | -0.0169965277777706 | | 8 | 25.74 | 25.7534548611111 | 25.4 | 0.353454861111111 | -0.0134548611111107 | | 9 | 25.78 | 25.8201215277778 | 25.3825 | 0.437621527777780 | -0.0401215277777816 | | 10 | 25.73 | 25.6634548611111 | 25.37875 | 0.28470486111111 | 0.0665451388888947 | | 11 | 24.67 | 24.9659548611111 | 25.3970833333333 | -0.431128472222223 | -0.295954861111106 | | 12 | 24.31 | 24.8111631944444 | 25.42875 | -0.617586805555558 | -0.501163194444445 | | 13 | 24.56 | 24.7724131944444 | 25.4641666666667 | -0.691753472222224 | -0.212413194444444 | | 14 | 25 | 25.0857465277778 | 25.5025 | -0.416753472222225 | -0.085746527777772 | | 15 | 25.38 | 25.2473090277778 | 25.5570833333333 | -0.309774305555555 | 0.132690972222225 | | 16 | 25.99 | 25.8318923611111 | 25.6329166666667 | 0.198975694444447 | 0.158107638888893 | | 17 | 26.22 | 26.1208506944444 | 25.7070833333333 | 0.413767361111111 | 0.0991493055555601 | | 18 | 26.19 | 26.1839756944444 | 25.78875 | 0.395225694444447 | 0.0060243055555631 | | 19 | 26.22 | 26.2636631944444 | 25.8804166666667 | 0.38324652777778 | -0.0436631944444379 | | 20 | 26.22 | 26.3134548611111 | 25.96 | 0.353454861111111 | -0.0934548611111055 | | 21 | 26.61 | 26.4601215277778 | 26.0225 | 0.437621527777780 | 0.149878472222227 | | 22 | 26.72 | 26.3738715277778 | 26.0891666666667 | 0.28470486111111 | 0.346128472222230 | | 23 | 25.46 | 25.7397048611111 | 26.1708333333333 | -0.431128472222223 | -0.279704861111107 | | 24 | 25.48 | 25.6357465277778 | 26.2533333333333 | -0.617586805555558 | -0.155746527777772 | | 25 | 25.59 | 25.6436631944444 | 26.3354166666667 | -0.691753472222224 | -0.053663194444443 | | 26 | 25.88 | 25.9994965277778 | 26.41625 | -0.416753472222225 | -0.119496527777777 | | 27 | 26 | 26.1739756944444 | 26.48375 | -0.309774305555555 | -0.17397569444444 | | 28 | 26.97 | 26.7173090277778 | 26.5183333333333 | 0.198975694444447 | 0.252690972222222 | | 29 | 27.2 | 26.9666840277778 | 26.5529166666667 | 0.413767361111111 | 0.233315972222218 | | 30 | 27.19 | 26.9914756944444 | 26.59625 | 0.395225694444447 | 0.198524305555559 | | 31 | 27.19 | 27.0136631944444 | 26.6304166666667 | 0.38324652777778 | 0.176336805555557 | | 32 | 27.19 | 27.0197048611111 | 26.66625 | 0.353454861111111 | 0.170295138888893 | | 33 | 27.26 | 27.1372048611111 | 26.6995833333333 | 0.437621527777780 | 0.122795138888893 | | 34 | 26.9 | 26.9809548611111 | 26.69625 | 0.28470486111111 | -0.0809548611111097 | | 35 | 26.11 | 26.2322048611111 | 26.6633333333333 | -0.431128472222223 | -0.122204861111111 | | 36 | 25.87 | 26.0203298611111 | 26.6379166666667 | -0.617586805555558 | -0.150329861111111 | | 37 | 26.02 | 25.9261631944444 | 26.6179166666667 | -0.691753472222224 | 0.0938368055555578 | | 38 | 26.31 | 26.1836631944444 | 26.6004166666667 | -0.416753472222225 | 0.126336805555557 | | 39 | 26.37 | 26.2723090277778 | 26.5820833333333 | -0.309774305555555 | 0.0976909722222246 | | 40 | 26.52 | 26.7652256944444 | 26.56625 | 0.198975694444447 | -0.245225694444443 | | 41 | 26.86 | 26.9854340277778 | 26.5716666666667 | 0.413767361111111 | -0.125434027777779 | | 42 | 26.92 | 26.9964756944444 | 26.60125 | 0.395225694444447 | -0.0764756944444436 | | 43 | 26.98 | 27.0140798611111 | 26.6308333333333 | 0.38324652777778 | -0.0340798611111062 | | 44 | 26.98 | 27.0047048611111 | 26.65125 | 0.353454861111111 | -0.0247048611111111 | | 45 | 27.03 | 27.1042881944444 | 26.6666666666667 | 0.437621527777780 | -0.074288194444442 | | 46 | 26.75 | 26.9772048611111 | 26.6925 | 0.28470486111111 | -0.227204861111112 | | 47 | 26.39 | 26.2955381944444 | 26.7266666666667 | -0.431128472222223 | 0.0944618055555573 | | 48 | 26.3 | 26.1415798611111 | 26.7591666666667 | -0.617586805555558 | 0.158420138888889 | | 49 | 26.3 | 26.1028298611111 | 26.7945833333333 | -0.691753472222224 | 0.197170138888890 | | 50 | 26.52 | 26.4161631944444 | 26.8329166666667 | -0.416753472222225 | 0.103836805555556 | | 51 | 26.53 | 26.5614756944444 | 26.87125 | -0.309774305555555 | -0.0314756944444419 | | 52 | 26.98 | 27.1206423611111 | 26.9216666666667 | 0.198975694444447 | -0.140642361111109 | | 53 | 27.22 | 27.4021006944444 | 26.9883333333333 | 0.413767361111111 | -0.182100694444443 | | 54 | 27.34 | 27.4431423611111 | 27.0479166666667 | 0.395225694444447 | -0.103142361111111 | | 55 | 27.41 | 27.4836631944444 | 27.1004166666667 | 0.38324652777778 | -0.0736631944444461 | | 56 | 27.47 | 27.4972048611111 | 27.14375 | 0.353454861111111 | -0.0272048611111124 | | 57 | 27.46 | 27.6334548611111 | 27.1958333333333 | 0.437621527777780 | -0.173454861111114 | | 58 | 27.53 | 27.5430381944444 | 27.2583333333333 | 0.28470486111111 | -0.0130381944444444 | | 59 | 27.21 | 26.8776215277778 | 27.30875 | -0.431128472222223 | 0.332378472222224 | | 60 | 26.91 | 26.7374131944444 | 27.355 | -0.617586805555558 | 0.172586805555554 | | 61 | 26.95 | 26.7061631944444 | 27.3979166666667 | -0.691753472222224 | 0.24383680555556 | | 62 | 26.91 | 27.0274131944444 | 27.4441666666667 | -0.416753472222225 | -0.117413194444435 | | 63 | 27.39 | 27.2018923611111 | 27.5116666666667 | -0.309774305555555 | 0.188107638888894 | | 64 | 27.62 | 27.8023090277778 | 27.6033333333333 | 0.198975694444447 | -0.182309027777777 | | 65 | 27.79 | 28.0971006944444 | 27.6833333333333 | 0.413767361111111 | -0.307100694444443 | | 66 | 27.88 | 28.1377256944444 | 27.7425 | 0.395225694444447 | -0.257725694444442 | | 67 | 27.9 | NA | NA | 0.38324652777778 | NA | | 68 | 28.09 | NA | NA | 0.353454861111111 | NA | | 69 | 28.46 | NA | NA | 0.437621527777780 | NA | | 70 | 28.73 | NA | NA | 0.28470486111111 | NA | | 71 | 27.93 | NA | NA | -0.431128472222223 | NA | | 72 | 27.61 | NA | NA | -0.617586805555558 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/1ymrz1211205156.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/1ymrz1211205156.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/2hhmv1211205156.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/2hhmv1211205156.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/3myhp1211205156.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/3myhp1211205156.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/4ghfp1211205156.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211205201a3m4zut0d1unjdz/4ghfp1211205156.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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