| Additief Decompositie Lederen Laarzen - Christine Van Bergen | | 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 11:22:28 -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/t12114770555b0cqe90xadlvrt.htm/, Retrieved Thu, 22 May 2008 19:24:15 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 101,22
101,25
101,25
101,26
101,26
101,26
101,29
101,31
101,31
101,31
101,32
101,34
101,34
101,34
101,34
101,34
101,34
101,34
101,34
101,39
102,16
102,19
102,31
102,32
102,32
102,32
102,36
102,36
102,37
102,37
102,37
102,37
103,45
103,8
103,81
103,81
103,81
103,84
103,9
103,91
103,92
103,92
103,93
104
104,51
105
105,01
105,01
105,01
105,01
105,13
105,14
105,15
105,22
105,23
105,23
105,57
106,05
106,09
106,09
106,19
106,2
106,2
106,22
106,22
106,23
106,23
106,61
106,95
107,74
107,8
107,8 | | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 101.22 | NA | NA | 0.113194444444445 | NA | | 2 | 101.25 | NA | NA | 0.0388194444444411 | NA | | 3 | 101.25 | NA | NA | 0.00861111111109973 | NA | | 4 | 101.26 | NA | NA | -0.0801388888889013 | NA | | 5 | 101.26 | NA | NA | -0.171701388888893 | NA | | 6 | 101.26 | NA | NA | -0.253368055555560 | NA | | 7 | 101.29 | 100.938298611111 | 101.286666666667 | -0.348368055555548 | 0.351701388888898 | | 8 | 101.31 | 100.875902777778 | 101.295416666667 | -0.419513888888887 | 0.434097222222235 | | 9 | 101.31 | 101.457152777778 | 101.302916666667 | 0.15423611111112 | -0.147152777777762 | | 10 | 101.31 | 101.700277777778 | 101.31 | 0.390277777777785 | -0.390277777777754 | | 11 | 101.32 | 101.650277777778 | 101.316666666667 | 0.333611111111117 | -0.330277777777766 | | 12 | 101.34 | 101.557673611111 | 101.323333333333 | 0.234340277777781 | -0.217673611111081 | | 13 | 101.34 | 101.441944444444 | 101.32875 | 0.113194444444445 | -0.101944444444428 | | 14 | 101.34 | 101.372986111111 | 101.334166666667 | 0.0388194444444411 | -0.0329861111110858 | | 15 | 101.34 | 101.381527777778 | 101.372916666667 | 0.00861111111109973 | -0.0415277777777305 | | 16 | 101.34 | 101.364861111111 | 101.445 | -0.0801388888889013 | -0.0248611111110932 | | 17 | 101.34 | 101.351215277778 | 101.522916666667 | -0.171701388888893 | -0.011215277777751 | | 18 | 101.34 | 101.351631944444 | 101.605 | -0.253368055555560 | -0.0116319444444315 | | 19 | 101.34 | 101.338298611111 | 101.686666666667 | -0.348368055555548 | 0.00170138888891813 | | 20 | 101.39 | 101.348819444444 | 101.768333333333 | -0.419513888888887 | 0.0411805555555702 | | 21 | 102.16 | 102.005902777778 | 101.851666666667 | 0.15423611111112 | 0.154097222222248 | | 22 | 102.19 | 102.326944444444 | 101.936666666667 | 0.390277777777785 | -0.136944444444424 | | 23 | 102.31 | 102.355694444444 | 102.022083333333 | 0.333611111111117 | -0.0456944444444218 | | 24 | 102.32 | 102.342256944444 | 102.107916666667 | 0.234340277777781 | -0.0222569444444360 | | 25 | 102.32 | 102.306944444444 | 102.19375 | 0.113194444444445 | 0.0130555555555532 | | 26 | 102.32 | 102.316319444444 | 102.2775 | 0.0388194444444411 | 0.00368055555554747 | | 27 | 102.36 | 102.380694444444 | 102.372083333333 | 0.00861111111109973 | -0.0206944444444446 | | 28 | 102.36 | 102.412777777778 | 102.492916666667 | -0.0801388888889013 | -0.0527777777777771 | | 29 | 102.37 | 102.450798611111 | 102.6225 | -0.171701388888893 | -0.0807986111111205 | | 30 | 102.37 | 102.493715277778 | 102.747083333333 | -0.253368055555560 | -0.123715277777791 | | 31 | 102.37 | 102.522881944444 | 102.87125 | -0.348368055555548 | -0.152881944444445 | | 32 | 102.37 | 102.577152777778 | 102.996666666667 | -0.419513888888887 | -0.207152777777779 | | 33 | 103.45 | 103.278402777778 | 103.124166666667 | 0.15423611111112 | 0.171597222222218 | | 34 | 103.8 | 103.643194444444 | 103.252916666667 | 0.390277777777785 | 0.156805555555550 | | 35 | 103.81 | 103.715694444444 | 103.382083333333 | 0.333611111111117 | 0.0943055555555503 | | 36 | 103.81 | 103.745590277778 | 103.51125 | 0.234340277777781 | 0.0644097222222229 | | 37 | 103.81 | 103.754027777778 | 103.640833333333 | 0.113194444444445 | 0.0559722222222234 | | 38 | 103.84 | 103.812569444444 | 103.77375 | 0.0388194444444411 | 0.0274305555555401 | | 39 | 103.9 | 103.894444444444 | 103.885833333333 | 0.00861111111109973 | 0.00555555555555998 | | 40 | 103.91 | 103.899861111111 | 103.98 | -0.0801388888889013 | 0.0101388888888749 | | 41 | 103.92 | 103.908298611111 | 104.08 | -0.171701388888893 | 0.0117013888888948 | | 42 | 103.92 | 103.926631944444 | 104.18 | -0.253368055555560 | -0.00663194444443604 | | 43 | 103.93 | 103.931631944444 | 104.28 | -0.348368055555548 | -0.00163194444442638 | | 44 | 104 | 103.959236111111 | 104.37875 | -0.419513888888887 | 0.0407638888889039 | | 45 | 104.51 | 104.632986111111 | 104.47875 | 0.15423611111112 | -0.122986111111089 | | 46 | 105 | 104.971527777778 | 104.58125 | 0.390277777777785 | 0.0284722222222342 | | 47 | 105.01 | 105.017361111111 | 104.68375 | 0.333611111111117 | -0.00736111111109494 | | 48 | 105.01 | 105.023506944444 | 104.789166666667 | 0.234340277777781 | -0.0135069444444156 | | 49 | 105.01 | 105.010694444444 | 104.8975 | 0.113194444444445 | -0.000694444444434339 | | 50 | 105.01 | 105.041736111111 | 105.002916666667 | 0.0388194444444411 | -0.031736111111087 | | 51 | 105.13 | 105.106944444444 | 105.098333333333 | 0.00861111111109973 | 0.0230555555555583 | | 52 | 105.14 | 105.106111111111 | 105.18625 | -0.0801388888889013 | 0.0338888888888960 | | 53 | 105.15 | 105.103298611111 | 105.275 | -0.171701388888893 | 0.0467013888888914 | | 54 | 105.22 | 105.111631944444 | 105.365 | -0.253368055555560 | 0.108368055555559 | | 55 | 105.23 | 105.110798611111 | 105.459166666667 | -0.348368055555548 | 0.119201388888897 | | 56 | 105.23 | 105.138402777778 | 105.557916666667 | -0.419513888888887 | 0.0915972222222194 | | 57 | 105.57 | 105.806319444444 | 105.652083333333 | 0.15423611111112 | -0.236319444444447 | | 58 | 106.05 | 106.131944444444 | 105.741666666667 | 0.390277777777785 | -0.0819444444444315 | | 59 | 106.09 | 106.164861111111 | 105.83125 | 0.333611111111117 | -0.0748611111110904 | | 60 | 106.09 | 106.152256944444 | 105.917916666667 | 0.234340277777781 | -0.0622569444444281 | | 61 | 106.19 | 106.114861111111 | 106.001666666667 | 0.113194444444445 | 0.0751388888888727 | | 62 | 106.2 | 106.139652777778 | 106.100833333333 | 0.0388194444444411 | 0.0603472222222337 | | 63 | 106.2 | 106.224444444444 | 106.215833333333 | 0.00861111111109973 | -0.0244444444444269 | | 64 | 106.22 | 106.263611111111 | 106.34375 | -0.0801388888889013 | -0.0436111111110904 | | 65 | 106.22 | 106.313715277778 | 106.485416666667 | -0.171701388888893 | -0.0937152777777612 | | 66 | 106.23 | 106.374548611111 | 106.627916666667 | -0.253368055555560 | -0.144548611111091 | | 67 | 106.23 | NA | NA | -0.348368055555548 | NA | | 68 | 106.61 | NA | NA | -0.419513888888887 | NA | | 69 | 106.95 | NA | NA | 0.15423611111112 | NA | | 70 | 107.74 | NA | NA | 0.390277777777785 | NA | | 71 | 107.8 | NA | NA | 0.333611111111117 | NA | | 72 | 107.8 | NA | NA | 0.234340277777781 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/1ixj81211476943.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/1ixj81211476943.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/2z7lo1211476943.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/2z7lo1211476943.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/3aukq1211476943.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/3aukq1211476943.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/4qp9d1211476943.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/22/t12114770555b0cqe90xadlvrt/4qp9d1211476943.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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