| Opgave 9-2 - Consumptieprijzen pakketreizen - Chloë De Rijck | | *Unverified author* | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Tue, 13 Jan 2009 10:41:48 -0700 | | | | Cite this page as follows: | | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt.htm/, Retrieved Tue, 13 Jan 2009 18:43:04 +0100 | | | | 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/Jan/13/t1231868584c07al8pn6gbu6wt.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 « | | 105,6
110,2
104,9
102,9
102,6
103,6
107,8
106,6
106
105,2
107,9
107,5
107,5
113,3
107,8
104,5
105,1
104,2
106,6
103,8
107,7
106,4
110
113,2
113,9
112
113,9
113,1
111,7
110,7
113,5
114
112,7
112,2
115,8
118,4
118,8
123,9
118
120,2
118,7
119,8
124,8
121,3
120,2
118,3
129,6
130,2
127,19
133,1
129,12
123,28
123,36
124,13
126,96
127,14
123,7
123,67
130,19
134,01
124,96
129,96
128,32
132,38
126,25
128,91
131,42
129,44
126,86
126,71
131,63
132,78
126,61
132,84
123,14
128,13
125,49
126,48
130,86
127,32
126,56
126,64
129,26
126,47
135,38
135,5
132,22
122,62
125,16
128,5
133,86
128,87
125,07
125,25
132,16
130,24 | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 105.6 | NA | NA | 0.357760416666667 | NA | | 2 | 110.2 | NA | NA | 4.41039930555555 | NA | | 3 | 104.9 | NA | NA | -0.0129340277777865 | NA | | 4 | 102.9 | NA | NA | -0.0862673611111124 | NA | | 5 | 102.6 | NA | NA | -2.21515625 | NA | | 6 | 103.6 | NA | NA | -1.89189236111111 | NA | | 7 | 107.8 | 107.081927083333 | 105.979166666667 | 1.10276041666666 | 0.718072916666657 | | 8 | 106.6 | 105.085815972222 | 106.1875 | -1.10168402777778 | 1.51418402777777 | | 9 | 106 | 104.132065972222 | 106.4375 | -2.30543402777778 | 1.86793402777778 | | 10 | 105.2 | 103.390815972222 | 106.625 | -3.23418402777777 | 1.80918402777779 | | 11 | 107.9 | 108.723177083333 | 106.795833333333 | 1.92734375000001 | -0.823177083333348 | | 12 | 107.5 | 109.974288194444 | 106.925 | 3.04928819444445 | -2.47428819444441 | | 13 | 107.5 | 107.257760416667 | 106.9 | 0.357760416666667 | 0.242239583333372 | | 14 | 113.3 | 111.143732638889 | 106.733333333333 | 4.41039930555555 | 2.15626736111113 | | 15 | 107.8 | 106.674565972222 | 106.6875 | -0.0129340277777865 | 1.12543402777779 | | 16 | 104.5 | 106.722065972222 | 106.808333333333 | -0.0862673611111124 | -2.22206597222220 | | 17 | 105.1 | 104.730677083333 | 106.945833333333 | -2.21515625 | 0.369322916666675 | | 18 | 104.2 | 105.378940972222 | 107.270833333333 | -1.89189236111111 | -1.17894097222221 | | 19 | 106.6 | 108.877760416667 | 107.775 | 1.10276041666666 | -2.27776041666665 | | 20 | 103.8 | 106.885815972222 | 107.9875 | -1.10168402777778 | -3.08581597222221 | | 21 | 107.7 | 105.882065972222 | 108.1875 | -2.30543402777778 | 1.81793402777781 | | 22 | 106.4 | 105.565815972222 | 108.8 | -3.23418402777777 | 0.83418402777778 | | 23 | 110 | 111.360677083333 | 109.433333333333 | 1.92734375000001 | -1.36067708333331 | | 24 | 113.2 | 113.028454861111 | 109.979166666667 | 3.04928819444445 | 0.171545138888888 | | 25 | 113.9 | 110.895260416667 | 110.5375 | 0.357760416666667 | 3.00473958333335 | | 26 | 112 | 115.660399305556 | 111.25 | 4.41039930555555 | -3.66039930555553 | | 27 | 113.9 | 111.870399305556 | 111.883333333333 | -0.0129340277777865 | 2.02960069444445 | | 28 | 113.1 | 112.247065972222 | 112.333333333333 | -0.0862673611111124 | 0.852934027777778 | | 29 | 111.7 | 110.601510416667 | 112.816666666667 | -2.21515625 | 1.09848958333335 | | 30 | 110.7 | 111.383107638889 | 113.275 | -1.89189236111111 | -0.68310763888887 | | 31 | 113.5 | 114.79859375 | 113.695833333333 | 1.10276041666666 | -1.29859374999997 | | 32 | 114 | 113.294149305556 | 114.395833333333 | -1.10168402777778 | 0.70585069444445 | | 33 | 112.7 | 112.757065972222 | 115.0625 | -2.30543402777778 | -0.0570659722222189 | | 34 | 112.2 | 112.294982638889 | 115.529166666667 | -3.23418402777777 | -0.0949826388888795 | | 35 | 115.8 | 118.044010416667 | 116.116666666667 | 1.92734375000001 | -2.24401041666665 | | 36 | 118.4 | 119.836788194444 | 116.7875 | 3.04928819444445 | -1.43678819444442 | | 37 | 118.8 | 117.995260416667 | 117.6375 | 0.357760416666667 | 0.804739583333316 | | 38 | 123.9 | 122.822899305556 | 118.4125 | 4.41039930555555 | 1.07710069444445 | | 39 | 118 | 119.016232638889 | 119.029166666667 | -0.0129340277777865 | -1.01623263888888 | | 40 | 120.2 | 119.509565972222 | 119.595833333333 | -0.0862673611111124 | 0.690434027777769 | | 41 | 118.7 | 118.20984375 | 120.425 | -2.21515625 | 0.490156249999998 | | 42 | 119.8 | 119.599774305556 | 121.491666666667 | -1.89189236111111 | 0.200225694444455 | | 43 | 124.8 | 123.435677083333 | 122.332916666667 | 1.10276041666666 | 1.36432291666668 | | 44 | 121.3 | 121.964149305556 | 123.065833333333 | -1.10168402777778 | -0.664149305555526 | | 45 | 120.2 | 121.607065972222 | 123.9125 | -2.30543402777778 | -1.40706597222221 | | 46 | 118.3 | 121.269982638889 | 124.504166666667 | -3.23418402777777 | -2.96998263888887 | | 47 | 129.6 | 126.754010416667 | 124.826666666667 | 1.92734375000001 | 2.84598958333333 | | 48 | 130.2 | 128.250538194444 | 125.20125 | 3.04928819444445 | 1.94946180555557 | | 49 | 127.19 | 125.829427083333 | 125.471666666667 | 0.357760416666667 | 1.36057291666668 | | 50 | 133.1 | 130.215399305556 | 125.805 | 4.41039930555555 | 2.88460069444446 | | 51 | 129.12 | 126.181232638889 | 126.194166666667 | -0.0129340277777865 | 2.93876736111113 | | 52 | 123.28 | 126.477482638889 | 126.56375 | -0.0862673611111124 | -3.19748263888887 | | 53 | 123.36 | 124.596927083333 | 126.812083333333 | -2.21515625 | -1.23692708333333 | | 54 | 124.13 | 125.103524305556 | 126.995416666667 | -1.89189236111111 | -0.973524305555571 | | 55 | 126.96 | 128.164010416667 | 127.06125 | 1.10276041666666 | -1.20401041666666 | | 56 | 127.14 | 125.735815972222 | 126.8375 | -1.10168402777778 | 1.40418402777777 | | 57 | 123.7 | 124.367899305556 | 126.673333333333 | -2.30543402777778 | -0.667899305555537 | | 58 | 123.67 | 123.784982638889 | 127.019166666667 | -3.23418402777777 | -0.114982638888904 | | 59 | 130.19 | 129.44609375 | 127.51875 | 1.92734375000001 | 0.743906250000009 | | 60 | 134.01 | 130.887621527778 | 127.838333333333 | 3.04928819444445 | 3.12237847222224 | | 61 | 124.96 | 128.58109375 | 128.223333333333 | 0.357760416666667 | -3.62109374999997 | | 62 | 129.96 | 132.915399305556 | 128.505 | 4.41039930555555 | -2.95539930555553 | | 63 | 128.32 | 128.719565972222 | 128.7325 | -0.0129340277777865 | -0.399565972222206 | | 64 | 132.38 | 128.904565972222 | 128.990833333333 | -0.0862673611111124 | 3.47543402777779 | | 65 | 126.25 | 126.96234375 | 129.1775 | -2.21515625 | -0.712343749999974 | | 66 | 128.91 | 127.294357638889 | 129.18625 | -1.89189236111111 | 1.61564236111113 | | 67 | 131.42 | 130.306510416667 | 129.20375 | 1.10276041666666 | 1.11348958333335 | | 68 | 129.44 | 128.290815972222 | 129.3925 | -1.10168402777778 | 1.14918402777781 | | 69 | 126.86 | 126.991232638889 | 129.296666666667 | -2.30543402777778 | -0.131232638888889 | | 70 | 126.71 | 125.669565972222 | 128.90375 | -3.23418402777777 | 1.04043402777779 | | 71 | 131.63 | 130.62234375 | 128.695 | 1.92734375000001 | 1.00765625000003 | | 72 | 132.78 | 131.611371527778 | 128.562083333333 | 3.04928819444445 | 1.16862847222225 | | 73 | 126.61 | 128.795260416667 | 128.4375 | 0.357760416666667 | -2.18526041666667 | | 74 | 132.84 | 132.736232638889 | 128.325833333333 | 4.41039930555555 | 0.103767361111096 | | 75 | 123.14 | 128.212065972222 | 128.225 | -0.0129340277777865 | -5.07206597222221 | | 76 | 128.13 | 128.123315972222 | 128.209583333333 | -0.0862673611111124 | 0.0066840277777942 | | 77 | 125.49 | 125.892760416667 | 128.107916666667 | -2.21515625 | -0.402760416666666 | | 78 | 126.48 | 125.854357638889 | 127.74625 | -1.89189236111111 | 0.625642361111133 | | 79 | 130.86 | 128.951510416667 | 127.84875 | 1.10276041666666 | 1.90848958333336 | | 80 | 127.32 | 127.223315972222 | 128.325 | -1.10168402777778 | 0.0966840277777976 | | 81 | 126.56 | 126.508732638889 | 128.814166666667 | -2.30543402777778 | 0.0512673611111154 | | 82 | 126.64 | 125.728732638889 | 128.962916666667 | -3.23418402777777 | 0.911267361111129 | | 83 | 129.26 | 130.646927083333 | 128.719583333333 | 1.92734375000001 | -1.38692708333332 | | 84 | 126.47 | 131.839288194444 | 128.79 | 3.04928819444445 | -5.36928819444444 | | 85 | 135.38 | 129.356927083333 | 128.999166666667 | 0.357760416666667 | 6.02307291666665 | | 86 | 135.5 | 133.599149305556 | 129.18875 | 4.41039930555555 | 1.90085069444447 | | 87 | 132.22 | 129.178315972222 | 129.19125 | -0.0129340277777865 | 3.04168402777779 | | 88 | 122.62 | 128.984982638889 | 129.07125 | -0.0862673611111124 | -6.36498263888885 | | 89 | 125.16 | 126.919010416667 | 129.134166666667 | -2.21515625 | -1.75901041666665 | | 90 | 128.5 | 127.520190972222 | 129.412083333333 | -1.89189236111111 | 0.979809027777776 | | 91 | 133.86 | NA | NA | 1.10276041666666 | NA | | 92 | 128.87 | NA | NA | -1.10168402777778 | NA | | 93 | 125.07 | NA | NA | -2.30543402777778 | NA | | 94 | 125.25 | NA | NA | -3.23418402777777 | NA | | 95 | 132.16 | NA | NA | 1.92734375000001 | NA | | 96 | 130.24 | NA | NA | 3.04928819444445 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/18pq11231868502.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/18pq11231868502.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/2a8xn1231868502.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/2a8xn1231868502.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/3ljf51231868502.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/3ljf51231868502.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/4na4h1231868502.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jan/13/t1231868584c07al8pn6gbu6wt/4na4h1231868502.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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