| modelu Classical Deomposition - opgave 9 - oef 2 - Toon Raeman | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Tue, 27 May 2008 07:53:39 -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/27/t12118965148r7v2miovzu3wf1.htm/, Retrieved Tue, 27 May 2008 15:55:14 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 117,99
118,13
117,06
118,03
118,57
118,44
118,02
118,18
116,79
116,91
117,19
117,3
116,35
117,04
116,26
115,91
115,75
115,21
115,07
114,17
113,96
113,59
114,47
113,52
113,56
113,59
113
112,07
111,11
109,61
109,51
109,21
108,86
107,99
108,74
108,74
107,74
107,8
106,96
106,73
106,27
105,69
105,39
105,09
104,94
104,75
104,38
103,65
103,49
103,39
103,48
103,33
103,61
103,21
102,85
103,25
102,88
102,51
101,99
101,6
101,21
100,74
100,36
100,26
100,37
100,23
100,02
99,8
99,58
99,69
99,53
99,37
| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 117.99 | NA | NA | -0.027482638888892 | NA | | 2 | 118.13 | NA | NA | 0.456059027777779 | NA | | 3 | 117.06 | NA | NA | 0.226475694444448 | NA | | 4 | 118.03 | NA | NA | 0.106371527777774 | NA | | 5 | 118.57 | NA | NA | 0.089704861111115 | NA | | 6 | 118.44 | NA | NA | -0.343420138888892 | NA | | 7 | 118.02 | 117.401996527778 | 117.649166666667 | -0.247170138888881 | 0.618003472222213 | | 8 | 118.18 | 117.340746527778 | 117.535416666667 | -0.194670138888893 | 0.839253472222254 | | 9 | 116.79 | 117.327413194444 | 117.456666666667 | -0.129253472222215 | -0.537413194444426 | | 10 | 116.91 | 117.084392361111 | 117.335 | -0.250607638888888 | -0.174392361111103 | | 11 | 117.19 | 117.386788194444 | 117.129166666667 | 0.257621527777782 | -0.196788194444451 | | 12 | 117.3 | 116.933454861111 | 116.877083333333 | 0.0563715277777623 | 0.366545138888910 | | 13 | 116.35 | 116.592100694444 | 116.619583333333 | -0.027482638888892 | -0.242100694444446 | | 14 | 117.04 | 116.785642361111 | 116.329583333333 | 0.456059027777779 | 0.254357638888905 | | 15 | 116.26 | 116.271059027778 | 116.044583333333 | 0.226475694444448 | -0.0110590277777476 | | 16 | 115.91 | 115.894704861111 | 115.788333333333 | 0.106371527777774 | 0.015295138888888 | | 17 | 115.75 | 115.626371527778 | 115.536666666667 | 0.089704861111115 | 0.123628472222222 | | 18 | 115.21 | 114.922413194444 | 115.265833333333 | -0.343420138888892 | 0.287586805555549 | | 19 | 115.07 | 114.744913194444 | 114.992083333333 | -0.247170138888881 | 0.325086805555557 | | 20 | 114.17 | 114.537413194444 | 114.732083333333 | -0.194670138888893 | -0.367413194444424 | | 21 | 113.96 | 114.323246527778 | 114.4525 | -0.129253472222215 | -0.363246527777775 | | 22 | 113.59 | 113.906059027778 | 114.156666666667 | -0.250607638888888 | -0.316059027777769 | | 23 | 114.47 | 114.060954861111 | 113.803333333333 | 0.257621527777782 | 0.409045138888885 | | 24 | 113.52 | 113.433038194444 | 113.376666666667 | 0.0563715277777623 | 0.0869618055555748 | | 25 | 113.56 | 112.884184027778 | 112.911666666667 | -0.027482638888892 | 0.675815972222239 | | 26 | 113.59 | 112.929392361111 | 112.473333333333 | 0.456059027777779 | 0.660607638888891 | | 27 | 113 | 112.280642361111 | 112.054166666667 | 0.226475694444448 | 0.719357638888908 | | 28 | 112.07 | 111.714704861111 | 111.608333333333 | 0.106371527777774 | 0.355295138888891 | | 29 | 111.11 | 111.225954861111 | 111.13625 | 0.089704861111115 | -0.115954861111106 | | 30 | 109.61 | 110.354913194444 | 110.698333333333 | -0.343420138888892 | -0.744913194444464 | | 31 | 109.51 | 110.009496527778 | 110.256666666667 | -0.247170138888881 | -0.499496527777779 | | 32 | 109.21 | 109.578246527778 | 109.772916666667 | -0.194670138888893 | -0.368246527777785 | | 33 | 108.86 | 109.150746527778 | 109.28 | -0.129253472222215 | -0.290746527777770 | | 34 | 107.99 | 108.555225694444 | 108.805833333333 | -0.250607638888888 | -0.565225694444436 | | 35 | 108.74 | 108.639288194444 | 108.381666666667 | 0.257621527777782 | 0.100711805555576 | | 36 | 108.74 | 108.073038194444 | 108.016666666667 | 0.0563715277777623 | 0.666961805555587 | | 37 | 107.74 | 107.654184027778 | 107.681666666667 | -0.027482638888892 | 0.0858159722222496 | | 38 | 107.8 | 107.794392361111 | 107.338333333333 | 0.456059027777779 | 0.00560763888888971 | | 39 | 106.96 | 107.229809027778 | 107.003333333333 | 0.226475694444448 | -0.269809027777782 | | 40 | 106.73 | 106.811371527778 | 106.705 | 0.106371527777774 | -0.0813715277777476 | | 41 | 106.27 | 106.478038194444 | 106.388333333333 | 0.089704861111115 | -0.208038194444441 | | 42 | 105.69 | 105.651163194444 | 105.994583333333 | -0.343420138888892 | 0.0388368055555759 | | 43 | 105.39 | 105.358246527778 | 105.605416666667 | -0.247170138888881 | 0.0317534722222206 | | 44 | 105.09 | 105.049913194444 | 105.244583333333 | -0.194670138888893 | 0.0400868055555748 | | 45 | 104.94 | 104.786579861111 | 104.915833333333 | -0.129253472222215 | 0.153420138888890 | | 46 | 104.75 | 104.378559027778 | 104.629166666667 | -0.250607638888888 | 0.371440972222231 | | 47 | 104.38 | 104.634288194444 | 104.376666666667 | 0.257621527777782 | -0.254288194444442 | | 48 | 103.65 | 104.218871527778 | 104.1625 | 0.0563715277777623 | -0.568871527777773 | | 49 | 103.49 | 103.925850694444 | 103.953333333333 | -0.027482638888892 | -0.43585069444444 | | 50 | 103.39 | 104.226892361111 | 103.770833333333 | 0.456059027777779 | -0.836892361111126 | | 51 | 103.48 | 103.834809027778 | 103.608333333333 | 0.226475694444448 | -0.35480902777779 | | 52 | 103.33 | 103.535538194444 | 103.429166666667 | 0.106371527777774 | -0.205538194444429 | | 53 | 103.61 | 103.325954861111 | 103.23625 | 0.089704861111115 | 0.284045138888899 | | 54 | 103.21 | 102.707829861111 | 103.05125 | -0.343420138888892 | 0.5021701388889 | | 55 | 102.85 | 102.623663194444 | 102.870833333333 | -0.247170138888881 | 0.226336805555562 | | 56 | 103.25 | 102.470746527778 | 102.665416666667 | -0.194670138888893 | 0.779253472222223 | | 57 | 102.88 | 102.295746527778 | 102.425 | -0.129253472222215 | 0.584253472222244 | | 58 | 102.51 | 101.916475694444 | 102.167083333333 | -0.250607638888888 | 0.593524305555576 | | 59 | 101.99 | 102.161788194444 | 101.904166666667 | 0.257621527777782 | -0.17178819444446 | | 60 | 101.6 | 101.701371527778 | 101.645 | 0.0563715277777623 | -0.101371527777786 | | 61 | 101.21 | 101.375434027778 | 101.402916666667 | -0.027482638888892 | -0.165434027777792 | | 62 | 100.74 | 101.597309027778 | 101.14125 | 0.456059027777779 | -0.857309027777788 | | 63 | 100.36 | 101.086475694444 | 100.86 | 0.226475694444448 | -0.726475694444446 | | 64 | 100.26 | 100.711371527778 | 100.605 | 0.106371527777774 | -0.451371527777752 | | 65 | 100.37 | 100.474704861111 | 100.385 | 0.089704861111115 | -0.104704861111102 | | 66 | 100.23 | 99.8461631944444 | 100.189583333333 | -0.343420138888892 | 0.383836805555561 | | 67 | 100.02 | NA | NA | -0.247170138888881 | NA | | 68 | 99.8 | NA | NA | -0.194670138888893 | NA | | 69 | 99.58 | NA | NA | -0.129253472222215 | NA | | 70 | 99.69 | NA | NA | -0.250607638888888 | NA | | 71 | 99.53 | NA | NA | 0.257621527777782 | NA | | 72 | 99.37 | NA | NA | 0.0563715277777623 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/1rzxu1211896414.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/1rzxu1211896414.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/2nlev1211896414.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/2nlev1211896414.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/3p6kd1211896414.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/3p6kd1211896414.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/4kda11211896414.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/27/t12118965148r7v2miovzu3wf1/4kda11211896414.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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