| | | *The author of this computation has been verified* | | R Software Module: /rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Sun, 19 Dec 2010 19:25:17 +0000 | | | | Cite this page as follows: | | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m.htm/, Retrieved Sun, 19 Dec 2010 20:22:59 +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/2010/Dec/19/t1292786574b3ps5t1j3c84h9m.htm/},
year = {2010},
}
@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 = {2010},
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 « | | 8,7000
8,9000
8,9000
8,1000
8,0000
8,3000
8,5000
8,7000
8,6000
8,3000
7,9000
7,9000
8,1000
8,3000
8,1000
7,4000
7,3000
7,7000
8,0000
8,0000
7,7000
6,9000
6,6000
6,9000
7,5000
7,9000
7,7000
6,5000
6,1000
6,4000
6,8000
7,1000
7,3000
7,2000
7,0000
7,0000
7,0000
7,3000
7,5000
7,2000
7,7000
8,0000
7,9000
8,0000
8,0000
7,9000
7,9000
8,0000
8,1000
8,1000
8,2000
8,0000
8,3000
8,5000
8,6000
8,7000
8,7000
8,5000
8,4000
8,5000
8,7000
8,7000
8,6000
7,9000
8,1000
8,2000
8,5000
8,6000
8,5000
8,3000
8,2000
8,7000
9,3000
9,3000
8,8000
7,4000
7,2000
7,5000
8,3000
8,8000
8,9000
8,6000
8,4000
8,4000
8,4000
8,4000
8,3000
7,6000
7,6000
7,9000
8,0000
8,2000
8,3000
8,2000
8,1000
8,0000
7,8000
7,6000
7,5000
6,8000
6,9000
7,1000
7,3000
7,4000
7,6000
7,6000
7,5000
7,5000
6,8000
6,4000
6,2000
6,0000
6,3000
6,3000
6,1000
6,1000
6,3000 | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 8.7 | NA | NA | 0.177300347222222 | NA | | 2 | 8.9 | NA | NA | 0.277821180555555 | NA | | 3 | 8.9 | NA | NA | 0.177300347222222 | NA | | 4 | 8.1 | NA | NA | -0.551345486111111 | NA | | 5 | 8 | NA | NA | -0.495616319444444 | NA | | 6 | 8.3 | NA | NA | -0.228949652777777 | NA | | 7 | 8.5 | 8.41740451388889 | 8.375 | 0.0424045138888889 | 0.0825954861111118 | | 8 | 8.7 | 8.55907118055556 | 8.325 | 0.234071180555556 | 0.140928819444444 | | 9 | 8.6 | 8.54552951388889 | 8.26666666666667 | 0.278862847222222 | 0.0544704861111107 | | 10 | 8.3 | 8.27521701388889 | 8.20416666666667 | 0.071050347222222 | 0.0247829861111128 | | 11 | 7.9 | 8.09188368055555 | 8.14583333333333 | -0.0539496527777776 | -0.191883680555554 | | 12 | 7.9 | 8.16271701388889 | 8.09166666666667 | 0.0710503472222219 | -0.262717013888887 | | 13 | 8.1 | 8.22313368055555 | 8.04583333333333 | 0.177300347222222 | -0.123133680555555 | | 14 | 8.3 | 8.27365451388889 | 7.99583333333333 | 0.277821180555555 | 0.0263454861111123 | | 15 | 8.1 | 8.10646701388889 | 7.92916666666667 | 0.177300347222222 | -0.00646701388888804 | | 16 | 7.4 | 7.28198784722222 | 7.83333333333333 | -0.551345486111111 | 0.118012152777779 | | 17 | 7.3 | 7.22521701388889 | 7.72083333333333 | -0.495616319444444 | 0.0747829861111118 | | 18 | 7.7 | 7.39605034722222 | 7.625 | -0.228949652777777 | 0.303949652777779 | | 19 | 8 | 7.60073784722222 | 7.55833333333333 | 0.0424045138888889 | 0.399262152777778 | | 20 | 8 | 7.75073784722222 | 7.51666666666667 | 0.234071180555556 | 0.249262152777778 | | 21 | 7.7 | 7.76219618055556 | 7.48333333333333 | 0.278862847222222 | -0.0621961805555564 | | 22 | 6.9 | 7.50021701388889 | 7.42916666666667 | 0.071050347222222 | -0.600217013888889 | | 23 | 6.6 | 7.28771701388889 | 7.34166666666667 | -0.0539496527777776 | -0.687717013888889 | | 24 | 6.9 | 7.30855034722222 | 7.2375 | 0.0710503472222219 | -0.408550347222222 | | 25 | 7.5 | 7.31063368055556 | 7.13333333333333 | 0.177300347222222 | 0.189366319444445 | | 26 | 7.9 | 7.32365451388889 | 7.04583333333333 | 0.277821180555555 | 0.576345486111111 | | 27 | 7.7 | 7.16896701388889 | 6.99166666666667 | 0.177300347222222 | 0.531032986111112 | | 28 | 6.5 | 6.43615451388889 | 6.9875 | -0.551345486111111 | 0.063845486111112 | | 29 | 6.1 | 6.52105034722222 | 7.01666666666667 | -0.495616319444444 | -0.421050347222223 | | 30 | 6.4 | 6.80855034722222 | 7.0375 | -0.228949652777777 | -0.408550347222222 | | 31 | 6.8 | 7.06323784722222 | 7.02083333333333 | 0.0424045138888889 | -0.263237847222221 | | 32 | 7.1 | 7.20907118055555 | 6.975 | 0.234071180555556 | -0.109071180555555 | | 33 | 7.3 | 7.22052951388889 | 6.94166666666667 | 0.278862847222222 | 0.079470486111111 | | 34 | 7.2 | 7.03355034722222 | 6.9625 | 0.071050347222222 | 0.166449652777780 | | 35 | 7 | 7.00438368055555 | 7.05833333333333 | -0.0539496527777776 | -0.00438368055555394 | | 36 | 7 | 7.26271701388889 | 7.19166666666667 | 0.0710503472222219 | -0.262717013888888 | | 37 | 7 | 7.48146701388889 | 7.30416666666667 | 0.177300347222222 | -0.481467013888888 | | 38 | 7.3 | 7.66532118055555 | 7.3875 | 0.277821180555555 | -0.365321180555554 | | 39 | 7.5 | 7.63146701388889 | 7.45416666666666 | 0.177300347222222 | -0.131467013888886 | | 40 | 7.2 | 6.96115451388889 | 7.5125 | -0.551345486111111 | 0.238845486111113 | | 41 | 7.7 | 7.08355034722222 | 7.57916666666667 | -0.495616319444444 | 0.61644965277778 | | 42 | 8 | 7.42938368055555 | 7.65833333333333 | -0.228949652777777 | 0.570616319444444 | | 43 | 7.9 | 7.78823784722222 | 7.74583333333333 | 0.0424045138888889 | 0.111762152777778 | | 44 | 8 | 8.05907118055556 | 7.825 | 0.234071180555556 | -0.0590711805555548 | | 45 | 8 | 8.16636284722222 | 7.8875 | 0.278862847222222 | -0.166362847222222 | | 46 | 7.9 | 8.02105034722222 | 7.95 | 0.071050347222222 | -0.121050347222222 | | 47 | 7.9 | 7.95438368055556 | 8.00833333333333 | -0.0539496527777776 | -0.0543836805555546 | | 48 | 8 | 8.12521701388889 | 8.05416666666667 | 0.0710503472222219 | -0.125217013888889 | | 49 | 8.1 | 8.28146701388889 | 8.10416666666667 | 0.177300347222222 | -0.181467013888891 | | 50 | 8.1 | 8.44032118055556 | 8.1625 | 0.277821180555555 | -0.340321180555556 | | 51 | 8.2 | 8.39813368055555 | 8.22083333333333 | 0.177300347222222 | -0.198133680555555 | | 52 | 8 | 7.72365451388889 | 8.275 | -0.551345486111111 | 0.276345486111110 | | 53 | 8.3 | 7.82521701388889 | 8.32083333333333 | -0.495616319444444 | 0.474782986111112 | | 54 | 8.5 | 8.13355034722222 | 8.3625 | -0.228949652777777 | 0.366449652777776 | | 55 | 8.6 | 8.45073784722222 | 8.40833333333333 | 0.0424045138888889 | 0.149262152777778 | | 56 | 8.7 | 8.69240451388889 | 8.45833333333333 | 0.234071180555556 | 0.00759548611111072 | | 57 | 8.7 | 8.77886284722222 | 8.5 | 0.278862847222222 | -0.0788628472222221 | | 58 | 8.5 | 8.58355034722222 | 8.5125 | 0.071050347222222 | -0.0835503472222214 | | 59 | 8.4 | 8.44605034722222 | 8.5 | -0.0539496527777776 | -0.04605034722222 | | 60 | 8.5 | 8.55021701388889 | 8.47916666666666 | 0.0710503472222219 | -0.0502170138888864 | | 61 | 8.7 | 8.63980034722222 | 8.4625 | 0.177300347222222 | 0.060199652777781 | | 62 | 8.7 | 8.73198784722222 | 8.45416666666667 | 0.277821180555555 | -0.0319878472222221 | | 63 | 8.6 | 8.61896701388889 | 8.44166666666667 | 0.177300347222222 | -0.0189670138888882 | | 64 | 7.9 | 7.87365451388889 | 8.425 | -0.551345486111111 | 0.0263454861111132 | | 65 | 8.1 | 7.91271701388889 | 8.40833333333333 | -0.495616319444444 | 0.187282986111112 | | 66 | 8.2 | 8.17938368055555 | 8.40833333333333 | -0.228949652777777 | 0.0206163194444446 | | 67 | 8.5 | 8.48407118055555 | 8.44166666666667 | 0.0424045138888889 | 0.0159288194444454 | | 68 | 8.6 | 8.72573784722222 | 8.49166666666667 | 0.234071180555556 | -0.125737847222224 | | 69 | 8.5 | 8.80386284722222 | 8.525 | 0.278862847222222 | -0.303862847222222 | | 70 | 8.3 | 8.58355034722222 | 8.5125 | 0.071050347222222 | -0.283550347222222 | | 71 | 8.2 | 8.40021701388889 | 8.45416666666667 | -0.0539496527777776 | -0.200217013888889 | | 72 | 8.7 | 8.45855034722222 | 8.3875 | 0.0710503472222219 | 0.241449652777778 | | 73 | 9.3 | 8.52730034722222 | 8.35 | 0.177300347222222 | 0.77269965277778 | | 74 | 9.3 | 8.62782118055556 | 8.35 | 0.277821180555555 | 0.672178819444445 | | 75 | 8.8 | 8.55230034722222 | 8.375 | 0.177300347222222 | 0.247699652777779 | | 76 | 7.4 | 7.85282118055556 | 8.40416666666667 | -0.551345486111111 | -0.452821180555556 | | 77 | 7.2 | 7.92938368055556 | 8.425 | -0.495616319444444 | -0.729383680555556 | | 78 | 7.5 | 8.19188368055556 | 8.42083333333333 | -0.228949652777777 | -0.691883680555555 | | 79 | 8.3 | 8.41323784722222 | 8.37083333333333 | 0.0424045138888889 | -0.113237847222221 | | 80 | 8.8 | 8.52990451388889 | 8.29583333333333 | 0.234071180555556 | 0.270095486111112 | | 81 | 8.9 | 8.51636284722222 | 8.2375 | 0.278862847222222 | 0.383637152777778 | | 82 | 8.6 | 8.29605034722222 | 8.225 | 0.071050347222222 | 0.303949652777778 | | 83 | 8.4 | 8.19605034722222 | 8.25 | -0.0539496527777776 | 0.203949652777778 | | 84 | 8.4 | 8.35438368055556 | 8.28333333333333 | 0.0710503472222219 | 0.0456163194444432 | | 85 | 8.4 | 8.46480034722222 | 8.2875 | 0.177300347222222 | -0.0648003472222225 | | 86 | 8.4 | 8.52782118055556 | 8.25 | 0.277821180555555 | -0.127821180555557 | | 87 | 8.3 | 8.37730034722222 | 8.2 | 0.177300347222222 | -0.0773003472222218 | | 88 | 7.6 | 7.60698784722222 | 8.15833333333333 | -0.551345486111111 | -0.00698784722222356 | | 89 | 7.6 | 7.63355034722222 | 8.12916666666667 | -0.495616319444444 | -0.0335503472222225 | | 90 | 7.9 | 7.87105034722222 | 8.1 | -0.228949652777777 | 0.0289496527777793 | | 91 | 8 | 8.10073784722222 | 8.05833333333333 | 0.0424045138888889 | -0.100737847222221 | | 92 | 8.2 | 8.23407118055555 | 8 | 0.234071180555556 | -0.0340711805555545 | | 93 | 8.3 | 8.21219618055556 | 7.93333333333333 | 0.278862847222222 | 0.0878038194444457 | | 94 | 8.2 | 7.93771701388889 | 7.86666666666667 | 0.071050347222222 | 0.262282986111112 | | 95 | 8.1 | 7.75021701388889 | 7.80416666666667 | -0.0539496527777776 | 0.349782986111111 | | 96 | 8 | 7.81271701388889 | 7.74166666666667 | 0.0710503472222219 | 0.187282986111111 | | 97 | 7.8 | 7.85646701388889 | 7.67916666666667 | 0.177300347222222 | -0.0564670138888888 | | 98 | 7.6 | 7.89448784722222 | 7.61666666666667 | 0.277821180555555 | -0.294487847222222 | | 99 | 7.5 | 7.73146701388889 | 7.55416666666667 | 0.177300347222222 | -0.231467013888889 | | 100 | 6.8 | 6.94865451388889 | 7.5 | -0.551345486111111 | -0.148654513888889 | | 101 | 6.9 | 6.95438368055556 | 7.45 | -0.495616319444444 | -0.0543836805555555 | | 102 | 7.1 | 7.17521701388889 | 7.40416666666667 | -0.228949652777777 | -0.0752170138888886 | | 103 | 7.3 | 7.38407118055556 | 7.34166666666667 | 0.0424045138888889 | -0.0840711805555552 | | 104 | 7.4 | 7.48407118055555 | 7.25 | 0.234071180555556 | -0.0840711805555543 | | 105 | 7.6 | 7.42469618055556 | 7.14583333333333 | 0.278862847222222 | 0.175303819444443 | | 106 | 7.6 | 7.12938368055556 | 7.05833333333333 | 0.071050347222222 | 0.470616319444444 | | 107 | 7.5 | 6.94605034722222 | 7 | -0.0539496527777776 | 0.553949652777779 | | 108 | 7.5 | 7.01271701388889 | 6.94166666666667 | 0.0710503472222219 | 0.487282986111111 | | 109 | 6.8 | NA | 6.85833333333333 | NA | NA | | 110 | 6.4 | NA | 6.75416666666667 | NA | NA | | 111 | 6.2 | NA | 6.64583333333333 | NA | NA | | 112 | 6 | NA | NA | NA | NA | | 113 | 6.3 | NA | NA | NA | NA | | 114 | 6.3 | NA | NA | NA | NA | | 115 | 6.1 | NA | NA | NA | NA | | 116 | 6.1 | NA | NA | NA | NA | | 117 | 6.3 | NA | NA | NA | NA |
| | | | Charts produced by software: |  | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/1ils41292786713.png (open in new window) | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/1ils41292786713.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/2sc971292786713.png (open in new window) | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/2sc971292786713.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/3sc971292786713.png (open in new window) | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/3sc971292786713.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/43lqa1292786713.png (open in new window) | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292786574b3ps5t1j3c84h9m/43lqa1292786713.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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,m$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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