*Unverified author*

R Software Module: /rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Mon, 16 May 2011 15:31:10 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb.htm/, Retrieved Mon, 16 May 2011 17:27:29 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

31.900 31.815 31.075 31.070 31.300 31.410 30.310 31.440 31.355 31.380 31.975 31.905 32.565 32.780 32.850 32.910 32.910 33.755 34.130 34.330 34.120 33.600 33.715 33.535 33.745 34.295 33.940 34.245 34.395 33.640 33.890 33.905 33.930 33.975 33.880 33.800 33.165 33.660 33.545 33.590 33.810 33.720 33.660 33.915 34.265 34.175 33.735 33.855 34.210 33.950 33.130 32.195 33.160 33.255 32.260 31.795 31.875 31.985 31.835 32.200 32.275 32.515 32.700 32.680 32.135 31.460 30.755 31.090 31.270 31.110 30.835 31.025 30.800 30.790

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Herman Ole Andreas Wold' @ www.yougetit.org Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 31.9 NA NA 0.0506527777777762 NA 2 31.815 NA NA 0.297861111111113 NA 3 31.075 NA NA 0.0944861111111137 NA 4 31.07 NA NA -0.0115555555555553 NA 5 31.3 NA NA 0.158194444444441 NA 6 31.41 NA NA 0.0590277777777785 NA 7 30.31 31.2930277777778 31.4389583333333 -0.145930555555557 -0.983027777777778 8 31.44 31.4602361111111 31.506875 -0.0466388888888922 -0.0202361111111031 9 31.355 31.4749444444444 31.6210416666667 -0.146097222222221 -0.119944444444442 10 31.38 31.7501527777778 31.7716666666667 -0.021513888888886 -0.370152777777779 11 31.975 31.7484444444444 31.9154166666667 -0.16697222222222 0.226555555555557 12 31.905 31.9586944444444 32.0802083333333 -0.12151388888889 -0.0536944444444387 13 32.565 32.3877361111111 32.3370833333333 0.0506527777777762 0.177263888888888 14 32.78 32.9145277777778 32.6166666666667 0.297861111111113 -0.134527777777777 15 32.85 32.9467777777778 32.8522916666667 0.0944861111111137 -0.0967777777777812 16 32.91 33.0484444444444 33.06 -0.0115555555555553 -0.138444444444445 17 32.91 33.3831944444444 33.225 0.158194444444441 -0.473194444444445 18 33.755 33.4244444444444 33.3654166666667 0.0590277777777785 0.330555555555563 19 34.13 33.3365694444444 33.4825 -0.145930555555557 0.79343055555556 20 34.33 33.5481527777778 33.5947916666667 -0.0466388888888922 0.781847222222225 21 34.12 33.5572361111111 33.7033333333333 -0.146097222222221 0.562763888888895 22 33.6 33.7828611111111 33.804375 -0.021513888888886 -0.182861111111109 23 33.715 33.7549027777778 33.921875 -0.16697222222222 -0.0399027777777761 24 33.535 33.8574444444444 33.9789583333333 -0.12151388888889 -0.322444444444443 25 33.745 34.0148194444444 33.9641666666667 0.0506527777777762 -0.269819444444444 26 34.295 34.2343194444444 33.9364583333333 0.297861111111113 0.0606805555555638 27 33.94 34.0053194444444 33.9108333333333 0.0944861111111137 -0.065319444444448 28 34.245 33.9069861111111 33.9185416666667 -0.0115555555555553 0.338013888888888 29 34.395 34.0992361111111 33.9410416666667 0.158194444444441 0.295763888888892 30 33.64 34.0179861111111 33.9589583333333 0.0590277777777785 -0.377986111111113 31 33.89 33.7999027777778 33.9458333333333 -0.145930555555557 0.0900972222222265 32 33.905 33.8485694444444 33.8952083333333 -0.0466388888888922 0.0564305555555578 33 33.93 33.7061944444444 33.8522916666667 -0.146097222222221 0.223805555555558 34 33.975 33.7870277777778 33.8085416666667 -0.021513888888886 0.187972222222214 35 33.88 33.5899027777778 33.756875 -0.16697222222222 0.290097222222229 36 33.8 33.6143194444444 33.7358333333333 -0.12151388888889 0.185680555555557 37 33.165 33.7802361111111 33.7295833333333 0.0506527777777762 -0.615236111111116 38 33.66 34.0182777777778 33.7204166666667 0.297861111111113 -0.358277777777779 39 33.545 33.8292777777778 33.7347916666667 0.0944861111111137 -0.284277777777774 40 33.59 33.7455277777778 33.7570833333333 -0.0115555555555553 -0.155527777777777 41 33.81 33.9175694444444 33.759375 0.158194444444441 -0.107569444444437 42 33.72 33.8146527777778 33.755625 0.0590277777777785 -0.0946527777777817 43 33.66 33.6555277777778 33.8014583333333 -0.145930555555557 0.0044722222222191 44 33.915 33.8104444444444 33.8570833333333 -0.0466388888888922 0.104555555555557 45 34.265 33.7057777777778 33.851875 -0.146097222222221 0.559222222222232 46 34.175 33.7549444444444 33.7764583333333 -0.021513888888886 0.420055555555557 47 33.735 33.5242777777778 33.69125 -0.16697222222222 0.210722222222223 48 33.855 33.5232777777778 33.6447916666667 -0.12151388888889 0.331722222222218 49 34.21 33.6177361111111 33.5670833333333 0.0506527777777762 0.592263888888894 50 33.95 33.7182777777778 33.4204166666667 0.297861111111113 0.231722222222224 51 33.13 33.3269861111111 33.2325 0.0944861111111137 -0.196986111111116 52 32.195 33.0301111111111 33.0416666666667 -0.0115555555555553 -0.835111111111111 53 33.16 33.0294444444444 32.87125 0.158194444444441 0.13055555555556 54 33.255 32.7821527777778 32.723125 0.0590277777777785 0.472847222222228 55 32.26 32.4276111111111 32.5735416666667 -0.145930555555557 -0.167611111111107 56 31.795 32.3864861111111 32.433125 -0.0466388888888922 -0.591486111111109 57 31.875 32.2093194444444 32.3554166666667 -0.146097222222221 -0.334319444444439 58 31.985 32.3361944444444 32.3577083333333 -0.021513888888886 -0.351194444444445 59 31.835 32.1682361111111 32.3352083333333 -0.16697222222222 -0.333236111111113 60 32.2 32.0961944444444 32.2177083333333 -0.12151388888889 0.103805555555567 61 32.275 32.1308611111111 32.0802083333333 0.0506527777777762 0.144138888888889 62 32.515 32.2859861111111 31.988125 0.297861111111113 0.229013888888897 63 32.7 32.0280277777778 31.9335416666667 0.0944861111111137 0.671972222222223 64 32.68 31.8603194444444 31.871875 -0.0115555555555553 0.819680555555554 65 32.135 31.9519444444444 31.79375 0.158194444444441 0.183055555555551 66 31.46 31.7621527777778 31.703125 0.0590277777777785 -0.302152777777778 67 30.755 31.4467777777778 31.5927083333333 -0.145930555555557 -0.691777777777773 68 31.09 31.4127361111111 31.459375 -0.0466388888888922 -0.322736111111109 69 31.27 NA NA -0.146097222222221 NA 70 31.11 NA NA -0.021513888888886 NA 71 30.835 NA NA -0.16697222222222 NA 72 31.025 NA NA -0.12151388888889 NA 73 30.8 NA NA NA NA 74 30.79 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/1hdwk1305559868.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/1hdwk1305559868.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/296131305559868.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/296131305559868.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/36fzp1305559868.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/36fzp1305559868.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/4yjxe1305559868.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t13055596459zo5dha6lbrenxb/4yjxe1305559868.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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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