| decomposition - sigaretten - caroline thys | | *Unverified author* | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Tue, 02 Jun 2009 09:41:09 -0600 | | | | Cite this page as follows: | | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl.htm/, Retrieved Tue, 02 Jun 2009 17:41:57 +0200 | | | | BibTeX entries for LaTeX users: | @Manual{KEY,
author = {{YOUR NAME}},
publisher = {Office for Research Development and Education},
title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl.htm/},
year = {2009},
}
@Manual{R,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2009},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}
| | | | Original text written by user: | | | | | IsPrivate? | | No (this computation is public) | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 106,07
106,07
106,07
106,07
106,07
106,2
107,5
108,31
108,53
108,61
108,62
108,62
108,62
108,62
110,1
110,74
110,77
110,77
110,78
110,78
110,78
110,84
110,84
110,84
110,84
110,84
111,01
112,66
114,04
114,16
114,2
114,2
114,23
114,23
114,23
114,23
114,23
114,23
115,97
116,96
117,08
117,08
117,08
117,63
119,12
119,47
119,5
119,52
119,49
119,49
119,5
119,5
119,56
122,35
122,92
122,92
123,04
123,04
123,04
123,06
123,33
128,21
129,57
129,79
131,66
135,01
136,01
136,31
136,37
136,4
136,4
136,4
137,34
142,18
143,79
144,08
144,08
144,09
144,09
144,11
144,11
144,15
144,15
144,16
144,2
144,38
144,38
144,28
144,46
144,53
144,53
145,34
147,98
150,42
150,53
150,64
| | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 106.07 | NA | NA | 0.990278534403955 | NA | | 2 | 106.07 | NA | NA | 0.997355460812724 | NA | | 3 | 106.07 | NA | NA | 1.00119351888841 | NA | | 4 | 106.07 | NA | NA | 1.00198095896971 | NA | | 5 | 106.07 | NA | NA | 1.00232897386216 | NA | | 6 | 106.2 | NA | NA | 1.00559762619841 | NA | | 7 | 107.5 | 107.950904746405 | 107.334583333333 | 1.00574205809472 | 0.995823057273446 | | 8 | 108.31 | 107.994496194066 | 107.547083333333 | 1.00416015801513 | 1.00292148041847 | | 9 | 108.53 | 108.122844611257 | 107.82125 | 1.00279717227594 | 1.00376567403685 | | 10 | 108.61 | 108.161526436307 | 108.18375 | 0.999794575768608 | 1.00414633168067 | | 11 | 108.62 | 108.160014732477 | 108.574166666667 | 0.996185538909441 | 1.00425282179058 | | 12 | 108.62 | 108.152521354594 | 108.960416666667 | 0.992585423800793 | 1.00432240172999 | | 13 | 108.62 | 108.225065328672 | 109.2875 | 0.990278534403955 | 1.00364919780948 | | 14 | 108.62 | 109.237434669390 | 109.527083333333 | 0.997355460812724 | 0.994347773991041 | | 15 | 110.1 | 109.854707368133 | 109.72375 | 1.00119351888841 | 1.00223288230194 | | 16 | 110.74 | 110.128144692427 | 109.910416666667 | 1.00198095896971 | 1.00555584868229 | | 17 | 110.77 | 110.352243651499 | 110.095833333333 | 1.00232897386216 | 1.00378566248114 | | 18 | 110.77 | 110.898144215182 | 110.280833333333 | 1.00559762619841 | 0.998844487289766 | | 19 | 110.78 | 111.100134565815 | 110.465833333333 | 1.00574205809472 | 0.997118504247851 | | 20 | 110.78 | 111.111158284506 | 110.650833333333 | 1.00416015801513 | 0.997019576704817 | | 21 | 110.78 | 111.091124241194 | 110.78125 | 1.00279717227594 | 0.997199378048252 | | 22 | 110.84 | 110.876385290592 | 110.899166666667 | 0.999794575768608 | 0.999671839134214 | | 23 | 110.84 | 110.691571233230 | 111.115416666667 | 0.996185538909441 | 1.00134092203332 | | 24 | 110.84 | 110.566985397990 | 111.392916666667 | 0.992585423800793 | 1.00246922353022 | | 25 | 110.84 | 110.591005793786 | 111.676666666667 | 0.990278534403955 | 1.00225148694893 | | 26 | 110.84 | 111.665579651694 | 111.961666666667 | 0.997355460812724 | 0.992606677417795 | | 27 | 111.01 | 112.381886675393 | 112.247916666667 | 1.00119351888841 | 0.98779263530825 | | 28 | 112.66 | 112.755839757325 | 112.532916666667 | 1.00198095896971 | 0.999150024002913 | | 29 | 114.04 | 113.078160823332 | 112.815416666667 | 1.00232897386216 | 1.00850596763924 | | 30 | 114.16 | 113.730996527985 | 113.097916666667 | 1.00559762619841 | 1.00377208927304 | | 31 | 114.2 | 114.031453605970 | 113.380416666667 | 1.00574205809472 | 1.00147806932825 | | 32 | 114.2 | 114.135772360461 | 113.662916666667 | 1.00416015801513 | 1.00056273014333 | | 33 | 114.23 | 114.329741275490 | 114.010833333333 | 1.00279717227594 | 0.999127599919516 | | 34 | 114.23 | 114.373166819343 | 114.396666666667 | 0.999794575768608 | 0.998748248183344 | | 35 | 114.23 | 114.264971776760 | 114.7025 | 0.996185538909441 | 0.999693941404646 | | 36 | 114.23 | 114.098521620421 | 114.950833333333 | 0.992585423800793 | 1.00115232325285 | | 37 | 114.23 | 114.072660074328 | 115.1925 | 0.990278534403955 | 1.0013792956662 | | 38 | 114.23 | 115.150090292908 | 115.455416666667 | 0.997355460812724 | 0.992009643322312 | | 39 | 115.97 | 115.940295307109 | 115.802083333333 | 1.00119351888841 | 1.00025620680724 | | 40 | 116.96 | 116.454401972122 | 116.224166666667 | 1.00198095896971 | 1.00434159653320 | | 41 | 117.08 | 116.933786276122 | 116.662083333333 | 1.00232897386216 | 1.00125039758426 | | 42 | 117.08 | 117.757577022888 | 117.102083333333 | 1.00559762619841 | 0.994246000639465 | | 43 | 117.08 | 118.216597745216 | 117.541666666667 | 1.00574205809472 | 0.990385463912047 | | 44 | 117.63 | 118.470815442625 | 117.98 | 1.00416015801513 | 0.992902763102595 | | 45 | 119.12 | 118.677284849462 | 118.34625 | 1.00279717227594 | 1.00373041185683 | | 46 | 119.47 | 118.574803524010 | 118.599166666667 | 0.999794575768608 | 1.00754963490881 | | 47 | 119.5 | 118.355143568599 | 118.808333333333 | 0.996185538909441 | 1.00967306022266 | | 48 | 119.52 | 118.247942269168 | 119.13125 | 0.992585423800793 | 1.01075754644369 | | 49 | 119.49 | 118.431536089929 | 119.594166666667 | 0.990278534403955 | 1.00893734848856 | | 50 | 119.49 | 119.740418801299 | 120.057916666667 | 0.997355460812724 | 0.997908652702189 | | 51 | 119.5 | 120.585416070785 | 120.441666666667 | 1.00119351888841 | 0.990998778242402 | | 52 | 119.5 | 120.992958224189 | 120.75375 | 1.00198095896971 | 0.98766078418033 | | 53 | 119.56 | 121.331922286014 | 121.05 | 1.00232897386216 | 0.985396075058982 | | 54 | 122.35 | 122.024243951045 | 121.345 | 1.00559762619841 | 1.00266960104326 | | 55 | 122.92 | 122.351035722367 | 121.6525 | 1.00574205809472 | 1.00465026122806 | | 56 | 122.92 | 122.684104105630 | 122.175833333333 | 1.00416015801513 | 1.00192279102570 | | 57 | 123.04 | 123.302686806585 | 122.95875 | 1.00279717227594 | 0.997869577594878 | | 58 | 123.04 | 123.781650358399 | 123.807083333333 | 0.999794575768608 | 0.99400839820562 | | 59 | 123.04 | 124.264184123564 | 124.74 | 0.996185538909441 | 0.99014853610316 | | 60 | 123.06 | 124.839123060465 | 125.771666666667 | 0.992585423800793 | 0.98574867383838 | | 61 | 123.33 | 125.611468080414 | 126.844583333333 | 0.990278534403955 | 0.981837103607824 | | 62 | 128.21 | 127.609553387111 | 127.947916666667 | 0.997355460812724 | 1.00470534217032 | | 63 | 129.57 | 129.215287039637 | 129.06125 | 1.00119351888841 | 1.00274513154356 | | 64 | 129.79 | 130.431201365617 | 130.173333333333 | 1.00198095896971 | 0.995083987888606 | | 65 | 131.66 | 131.592429881783 | 131.286666666667 | 1.00232897386216 | 1.00051348028361 | | 66 | 135.01 | 133.140287710647 | 132.399166666667 | 1.00559762619841 | 1.01404317447035 | | 67 | 136.01 | 134.305537260396 | 133.53875 | 1.00574205809472 | 1.01269093422634 | | 68 | 136.31 | 135.264975685362 | 134.704583333333 | 1.00416015801513 | 1.00772575686605 | | 69 | 136.37 | 136.259244104545 | 135.879166666667 | 1.00279717227594 | 1.00081283215816 | | 70 | 136.4 | 137.038926433090 | 137.067083333333 | 0.999794575768608 | 0.995337628149018 | | 71 | 136.4 | 137.652917766507 | 138.18 | 0.996185538909441 | 0.990897993396465 | | 72 | 136.4 | 138.044644969615 | 139.075833333333 | 0.992585423800793 | 0.988086137133554 | | 73 | 137.34 | 138.431861556441 | 139.790833333333 | 0.990278534403955 | 0.99211264268092 | | 74 | 142.18 | 140.081067859799 | 140.4525 | 0.997355460812724 | 1.0149836960288 | | 75 | 143.79 | 141.268405515155 | 141.1 | 1.00119351888841 | 1.01784967045993 | | 76 | 144.08 | 142.026208521228 | 141.745416666667 | 1.00198095896971 | 1.01446065131328 | | 77 | 144.08 | 142.722875499450 | 142.39125 | 1.00232897386216 | 1.00950880856205 | | 78 | 144.09 | 143.838170457354 | 143.0375 | 1.00559762619841 | 1.00175078382772 | | 79 | 144.09 | 144.471494171779 | 143.646666666667 | 1.00574205809472 | 0.997359381004772 | | 80 | 144.11 | 144.623329957997 | 144.024166666667 | 1.00416015801513 | 0.996450572959795 | | 81 | 144.11 | 144.543602244009 | 144.140416666667 | 1.00279717227594 | 0.997000197606273 | | 82 | 144.15 | 144.143716637146 | 144.173333333333 | 0.999794575768608 | 1.00004359095908 | | 83 | 144.15 | 143.647464246894 | 144.1975 | 0.996185538909441 | 1.00349839626993 | | 84 | 144.16 | 143.162249983828 | 144.231666666667 | 0.992585423800793 | 1.00696936529207 | | 85 | 144.2 | 142.865833694235 | 144.268333333333 | 0.990278534403955 | 1.00933859601884 | | 86 | 144.38 | 143.956209389832 | 144.337916666667 | 0.997355460812724 | 1.00294388558829 | | 87 | 144.38 | 144.722940319286 | 144.550416666667 | 1.00119351888841 | 0.997630366557438 | | 88 | 144.28 | 145.260102066303 | 144.972916666667 | 1.00198095896971 | 0.99325277862014 | | 89 | 144.46 | 145.838865696944 | 145.5 | 1.00232897386216 | 0.990545279611475 | | 90 | 144.53 | 146.853287339906 | 146.035833333333 | 1.00559762619841 | 0.98417953467716 | | 91 | 144.53 | NA | NA | 1.00574205809472 | NA | | 92 | 145.34 | NA | NA | 1.00416015801513 | NA | | 93 | 147.98 | NA | NA | 1.00279717227594 | NA | | 94 | 150.42 | NA | NA | 0.999794575768608 | NA | | 95 | 150.53 | NA | NA | 0.996185538909441 | NA | | 96 | 150.64 | NA | NA | 0.992585423800793 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/1xegr1243957267.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/1xegr1243957267.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/21zss1243957267.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/21zss1243957267.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/3yw7r1243957267.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/3yw7r1243957267.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/44f021243957267.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243957311gdbuzyrjdjpwxrl/44f021243957267.ps (open in new window) |
| | | | Parameters (Session): | | par1 = multiplicative ; par2 = 12 ; | | | | Parameters (R input): | | par1 = multiplicative ; 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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