| Classical Deomposition - blazers - Wouter Dewachter | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Tue, 20 May 2008 06:39:33 -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/20/t1211287254sws6tl3st30xioe.htm/, Retrieved Tue, 20 May 2008 14:40:59 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 161,79
161,79
161,85
161,77
161,86
161,89
161,89
161,89
162,18
162,43
162,58
162,57
162,57
162,57
162,44
162,79
163,15
163,23
163,23
163,23
163,38
163,71
163,73
163,73
163,73
163,73
163,93
164,27
164,57
164,73
164,73
164,76
165,75
165,86
165,99
166,13
166,13
166,13
166,15
166,45
166,48
166,51
166,51
166,51
166,58
166,82
167,35
167,5
167,5
167,6
167,72
167,29
166,98
166,98
166,98
166,98
167,63
167,83
167,85
167,87
167,87
167,96
167,7
169,25
168,79
168,77
168,77
169
168,92
169,23
169,28
169,29
| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 161.79 | NA | NA | 0.088480902777769 | NA | | 2 | 161.79 | NA | NA | 0.00743923611110494 | NA | | 3 | 161.85 | NA | NA | -0.0498524305555523 | NA | | 4 | 161.77 | NA | NA | -0.0228732638889101 | NA | | 5 | 161.86 | NA | NA | -0.0390190972222288 | NA | | 6 | 161.89 | NA | NA | -0.0816232638889064 | NA | | 7 | 161.89 | 161.881293402778 | 162.073333333333 | -0.192039930555558 | 0.0087065972222149 | | 8 | 161.89 | 161.842439236111 | 162.138333333333 | -0.295894097222208 | 0.0475607638888675 | | 9 | 162.18 | 162.253585069444 | 162.195416666667 | 0.0581684027777823 | -0.073585069444448 | | 10 | 162.43 | 162.418585069444 | 162.2625 | 0.156085069444467 | 0.0114149305555316 | | 11 | 162.58 | 162.563793402778 | 162.35875 | 0.205043402777791 | 0.0162065972222081 | | 12 | 162.57 | 162.634418402778 | 162.468333333333 | 0.166085069444450 | -0.0644184027777897 | | 13 | 162.57 | 162.668480902778 | 162.58 | 0.088480902777769 | -0.0984809027777942 | | 14 | 162.57 | 162.699105902778 | 162.691666666667 | 0.00743923611110494 | -0.129105902777752 | | 15 | 162.44 | 162.747647569444 | 162.7975 | -0.0498524305555523 | -0.307647569444441 | | 16 | 162.79 | 162.877960069444 | 162.900833333333 | -0.0228732638889101 | -0.0879600694444775 | | 17 | 163.15 | 162.963064236111 | 163.002083333333 | -0.0390190972222288 | 0.186935763888897 | | 18 | 163.23 | 163.016710069444 | 163.098333333333 | -0.0816232638889064 | 0.213289930555533 | | 19 | 163.23 | 163.002960069444 | 163.195 | -0.192039930555558 | 0.227039930555549 | | 20 | 163.23 | 162.995772569444 | 163.291666666667 | -0.295894097222208 | 0.234227430555563 | | 21 | 163.38 | 163.460251736111 | 163.402083333333 | 0.0581684027777823 | -0.0802517361111086 | | 22 | 163.71 | 163.681918402778 | 163.525833333333 | 0.156085069444467 | 0.0280815972222399 | | 23 | 163.73 | 163.851710069444 | 163.646666666667 | 0.205043402777791 | -0.121710069444447 | | 24 | 163.73 | 163.934418402778 | 163.768333333333 | 0.166085069444450 | -0.204418402777776 | | 25 | 163.73 | 163.981814236111 | 163.893333333333 | 0.088480902777769 | -0.25181423611113 | | 26 | 163.73 | 164.027022569444 | 164.019583333333 | 0.00743923611110494 | -0.297022569444465 | | 27 | 163.93 | 164.132230902778 | 164.182083333333 | -0.0498524305555523 | -0.202230902777785 | | 28 | 164.27 | 164.347543402778 | 164.370416666667 | -0.0228732638889101 | -0.0775434027777635 | | 29 | 164.57 | 164.515147569444 | 164.554166666667 | -0.0390190972222288 | 0.0548524305555418 | | 30 | 164.73 | 164.666710069444 | 164.748333333333 | -0.0816232638889064 | 0.0632899305555554 | | 31 | 164.73 | 164.756293402778 | 164.948333333333 | -0.192039930555558 | -0.0262934027777817 | | 32 | 164.76 | 164.852439236111 | 165.148333333333 | -0.295894097222208 | -0.0924392361111188 | | 33 | 165.75 | 165.399001736111 | 165.340833333333 | 0.0581684027777823 | 0.350998263888869 | | 34 | 165.86 | 165.680251736111 | 165.524166666667 | 0.156085069444467 | 0.179748263888882 | | 35 | 165.99 | 165.899626736111 | 165.694583333333 | 0.205043402777791 | 0.090373263888921 | | 36 | 166.13 | 166.014418402778 | 165.848333333333 | 0.166085069444450 | 0.115581597222217 | | 37 | 166.13 | 166.085147569444 | 165.996666666667 | 0.088480902777769 | 0.0448524305555509 | | 38 | 166.13 | 166.151189236111 | 166.14375 | 0.00743923611110494 | -0.0211892361111268 | | 39 | 166.15 | 166.201397569444 | 166.25125 | -0.0498524305555523 | -0.0513975694444468 | | 40 | 166.45 | 166.302960069444 | 166.325833333333 | -0.0228732638889101 | 0.147039930555536 | | 41 | 166.48 | 166.383480902778 | 166.4225 | -0.0390190972222288 | 0.0965190972222274 | | 42 | 166.51 | 166.454626736111 | 166.53625 | -0.0816232638889064 | 0.055373263888896 | | 43 | 166.51 | 166.458376736111 | 166.650416666667 | -0.192039930555558 | 0.0516232638888710 | | 44 | 166.51 | 166.472855902778 | 166.76875 | -0.295894097222208 | 0.0371440972221819 | | 45 | 166.58 | 166.953585069444 | 166.895416666667 | 0.0581684027777823 | -0.373585069444459 | | 46 | 166.82 | 167.151918402778 | 166.995833333333 | 0.156085069444467 | -0.331918402777774 | | 47 | 167.35 | 167.256710069444 | 167.051666666667 | 0.205043402777791 | 0.0932899305555566 | | 48 | 167.5 | 167.258168402778 | 167.092083333333 | 0.166085069444450 | 0.241831597222244 | | 49 | 167.5 | 167.219730902778 | 167.13125 | 0.088480902777769 | 0.280269097222259 | | 50 | 167.6 | 167.177855902778 | 167.170416666667 | 0.00743923611110494 | 0.42214409722223 | | 51 | 167.72 | 167.183897569444 | 167.23375 | -0.0498524305555523 | 0.536102430555559 | | 52 | 167.29 | 167.296710069444 | 167.319583333333 | -0.0228732638889101 | -0.00671006944443775 | | 53 | 166.98 | 167.343480902778 | 167.3825 | -0.0390190972222288 | -0.363480902777781 | | 54 | 166.98 | 167.337126736111 | 167.41875 | -0.0816232638889064 | -0.357126736111098 | | 55 | 166.98 | 167.257543402778 | 167.449583333333 | -0.192039930555558 | -0.277543402777752 | | 56 | 166.98 | 167.184105902778 | 167.48 | -0.295894097222208 | -0.204105902777741 | | 57 | 167.63 | 167.552335069444 | 167.494166666667 | 0.0581684027777823 | 0.0776649305555566 | | 58 | 167.83 | 167.731085069444 | 167.575 | 0.156085069444467 | 0.098914930555594 | | 59 | 167.85 | 167.937126736111 | 167.732083333333 | 0.205043402777791 | -0.0871267361111165 | | 60 | 167.87 | 168.048168402778 | 167.882083333333 | 0.166085069444450 | -0.178168402777771 | | 61 | 167.87 | 168.119730902778 | 168.03125 | 0.088480902777769 | -0.249730902777770 | | 62 | 167.96 | 168.197439236111 | 168.19 | 0.00743923611110494 | -0.237439236111129 | | 63 | 167.7 | 168.278064236111 | 168.327916666667 | -0.0498524305555523 | -0.578064236111146 | | 64 | 169.25 | 168.417126736111 | 168.44 | -0.0228732638889101 | 0.83287326388887 | | 65 | 168.79 | 168.518897569444 | 168.557916666667 | -0.0390190972222288 | 0.271102430555544 | | 66 | 168.77 | 168.595043402778 | 168.676666666667 | -0.0816232638889064 | 0.174956597222234 | | 67 | 168.77 | NA | NA | -0.192039930555558 | NA | | 68 | 169 | NA | NA | -0.295894097222208 | NA | | 69 | 168.92 | NA | NA | 0.0581684027777823 | NA | | 70 | 169.23 | NA | NA | 0.156085069444467 | NA | | 71 | 169.28 | NA | NA | 0.205043402777791 | NA | | 72 | 169.29 | NA | NA | 0.166085069444450 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/1j1e31211287171.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/1j1e31211287171.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/2pkpp1211287171.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/2pkpp1211287171.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/3j0on1211287171.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/3j0on1211287171.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/4f9xv1211287171.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/20/t1211287254sws6tl3st30xioe/4f9xv1211287171.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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