seizoen

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 07 May 2008 11:14:35 -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/07/t1210180583e6lbacojuupsiqk.htm/, Retrieved Wed, 07 May 2008 19:16:29 +0200

User-defined keywords:

Dataseries X:

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56421 53152 53536 52408 41454 38271 35306 26414 31917 38030 27534 18387 50556 43901 48572 43899 37532 40357 35489 29027 34485 42598 30306 26451 47460 50104 61465 53726 39477 43895 31481 29896 33842 39120 33702 25094 51442 45594 52518 48564 41745 49585 32747 33379 35645 37034 35681 20972 58552 54955 65540 51570 51145 46641 35704 33253 35193 41668 34865 21210 56126 49231 59723 48103 47472 50497 40059 34149 36860 46356 36577

Text written by user:

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 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 56421 NA NA 2526.09166666667 NA 2 53152 NA NA 3471.275 NA 3 53536 52775.3083333333 52008.375 766.933333333333 760.691666666666 4 52408 41513.075 48277.375 -6764.3 10894.925 5 41454 46664.5916666667 44138.5 2526.09166666667 -5210.59166666667 6 38271 42081.775 38610.5 3471.275 -3810.775 7 35306 34936.0583333333 34169.125 766.933333333333 369.941666666666 8 26414 26182.575 32946.875 -6764.3 231.425000000003 9 31917 34471.3416666667 31945.25 2526.09166666667 -2554.34166666667 10 38030 33441.65 29970.375 3471.275 4588.35 11 27534 32063.8083333333 31296.875 766.933333333333 -4529.80833333333 12 18387 27596.325 34360.625 -6764.3 -9209.325 13 50556 40250.3416666667 37724.25 2526.09166666667 10305.6583333333 14 43901 47014.275 43543 3471.275 -3113.275 15 48572 45870.9333333333 45104 766.933333333333 2701.06666666667 16 43899 36268.7 43033 -6764.3 7630.3 17 37532 43480.7166666667 40954.625 2526.09166666667 -5948.71666666667 18 40357 40931.525 37460.25 3471.275 -574.525000000001 19 35489 35987.3083333333 35220.375 766.933333333333 -498.308333333334 20 29027 28355.325 35119.625 -6764.3 671.675000000003 21 34485 37277.9666666667 34751.875 2526.09166666667 -2792.96666666667 22 42598 37253.275 33782 3471.275 5344.725 23 30306 35848.8083333333 35081.875 766.933333333333 -5542.80833333333 24 26451 30877.7 37642 -6764.3 -4426.7 25 47460 45001.2166666667 42475.125 2526.09166666667 2458.78333333333 26 50104 53250.65 49779.375 3471.275 -3146.65 27 61465 52957.8083333333 52190.875 766.933333333333 8507.19166666667 28 53726 43652.575 50416.875 -6764.3 10073.425 29 39477 48418.8416666667 45892.75 2526.09166666667 -8941.84166666667 30 43895 42637.275 39166 3471.275 1257.72500000000 31 31481 36249.8083333333 35482.875 766.933333333333 -4768.80833333333 32 29896 27417.325 34181.625 -6764.3 2478.67500000000 33 33842 36388.4666666667 33862.375 2526.09166666667 -2546.46666666667 34 39120 37011.025 33539.75 3471.275 2108.975 35 33702 35906.4333333333 35139.5 766.933333333333 -2204.43333333333 36 25094 31384.45 38148.75 -6764.3 -6290.45 37 51442 43836.0916666667 41310 2526.09166666667 7605.90833333333 38 45594 50067.025 46595.75 3471.275 -4473.025 39 52518 49084.3083333333 48317.375 766.933333333333 3433.69166666667 40 48564 40839.825 47604.125 -6764.3 7724.175 41 41745 48157.7166666667 45631.625 2526.09166666667 -6412.71666666667 42 49585 44733.4 41262.125 3471.275 4851.6 43 32747 39368.4333333333 38601.5 766.933333333333 -6621.43333333333 44 33379 29505.825 36270.125 -6764.3 3873.175 45 35645 37594.0916666667 35068 2526.09166666667 -1949.09166666667 46 37034 37355.15 33883.875 3471.275 -321.150000000001 47 35681 35963.3083333333 35196.375 766.933333333333 -282.308333333334 48 20972 33535.575 40299.875 -6764.3 -12563.575 49 58552 48798.4666666667 46272.375 2526.09166666667 9753.53333333333 50 54955 57300.775 53829.5 3471.275 -2345.775 51 65540 57495.3083333333 56728.375 766.933333333333 8044.69166666667 52 51570 47998.95 54763.25 -6764.3 3571.05 53 51145 52520.5916666667 49994.5 2526.09166666667 -1375.59166666667 54 46641 47446.65 43975.375 3471.275 -805.650000000001 55 35704 40458.6833333333 39691.75 766.933333333333 -4754.68333333333 56 33253 30311.825 37076.125 -6764.3 2941.175 57 35193 38875.7166666667 36349.625 2526.09166666667 -3682.71666666667 58 41668 38210.65 34739.375 3471.275 3457.35 59 34865 36617.5583333333 35850.625 766.933333333333 -1752.55833333333 60 21210 32648.325 39412.625 -6764.3 -11438.325 61 56126 45991.3416666667 43465.25 2526.09166666667 10134.6583333333 62 49231 53405.4 49934.125 3471.275 -4174.4 63 59723 52980.9333333333 52214 766.933333333333 6742.06666666667 64 48103 44526.2 51290.5 -6764.3 3576.8 65 47472 51516.8416666667 48990.75 2526.09166666667 -4044.84166666667 66 50497 48259.775 44788.5 3471.275 2237.225 67 40059 42484.6833333333 41717.75 766.933333333333 -2425.68333333333 68 34149 33109.325 39873.625 -6764.3 1039.67500000000 69 36860 NA 38920.75 NA NA 70 46356 NA NA NA NA 71 36577 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/18vda1210180472.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/18vda1210180472.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/2a0d01210180472.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/2a0d01210180472.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/38uvd1210180472.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/38uvd1210180472.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/4xzuf1210180472.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/07/t1210180583e6lbacojuupsiqk/4xzuf1210180472.ps (open in new window)

Parameters (Session):

par1 = additive ; par2 = 4 ;

Parameters (R input):

par1 = additive ; par2 = 4 ;

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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