KDGP2W52

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 12 Jan 2010 06:40:16 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et.htm/, Retrieved Tue, 12 Jan 2010 14:41:21 +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/Jan/12/t1263303675z83buikdoeyv8et.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:

Classical decomposition maandelijkse bezokers VS

Dataseries X:

» Textbox « » Textfile « » CSV «

2357402 2199181 2603060 2629720 2638792 2717481 3810804 3871664 2998364 2923432 2712359 2996099 2395029 2483862 3120231 3360606 3177203 3062783 4242509 4026394 3192481 3118695 2782482 3209833 2630190 2592882 3785309 3231539 3421369 3312134 4647303 4289177 3463853 3304422 3006121 3464238 2921118 2624018 3500718 3939351 3467672 3343628 4852445 4597807 3653145 3572079 3334861 3695369 3075704 2852998 3942704 4004560 3822145 3760085 5267816 5271333 4144142 4109749 3896808 4211074 3402318 3279817 4706628 4079499 4344530 4048625 5394915 5611967 4145481 4025610 3552218 3910443

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 2357402 NA NA 0.801187255272192 NA 2 2199181 NA NA 0.764307105895857 NA 3 2603060 NA NA 1.04250046166845 NA 4 2629720 NA NA 1.01803762623020 NA 5 2638792 NA NA 0.98990679466426 NA 6 2717481 NA NA 0.948422064907969 NA 7 3810804 3807094.55842742 2873097.625 1.32508360499147 1.00097434973459 8 3871664 3679723.73519271 2886527.125 1.27479270966238 1.05216159652737 9 2998364 2921276.02408093 2919937.625 1.00045836564092 1.02638846013989 10 2923432 2873700.96041435 2971940 0.96694447411938 1.01730557224663 11 2712359 2677223.52651611 3024827.375 0.885083079002521 1.01312384757413 12 2996099 3010447.13836991 3061648.75 0.983276457944404 0.995233884632274 13 2395029 2478892.62968909 3094024.04166667 0.801187255272192 0.966168914020447 14 2483862 2383460.24576037 3118458.83333333 0.764307105895857 1.04212436704922 15 3120231 3266147.82171706 3132994.125 1.04250046166845 0.955324489373434 16 3360606 3206022.71412905 3149218.29166667 1.01803762623020 1.04821652859467 17 3177203 3128378.72666051 3160276.04166667 0.98990679466426 1.01560689341204 18 3062783 3008492.87253662 3172103.41666667 0.948422064907969 1.01804562276314 19 4242509 4228086.53929836 3190807.375 1.32508360499147 1.00341110820878 20 4026394 4085899.62248713 3205148.25 1.27479270966238 0.9854363474424 21 3192481 3238886.24732876 3237402.33333333 1.00045836564092 0.985672467698724 22 3118695 3151983.83315607 3259736.125 0.96694447411938 0.9894387677989 23 2782482 2889381.96030534 3264531.91666667 0.885083079002521 0.963002482269932 24 3209833 3230156.69852043 3285095.125 0.983276457944404 0.993708138515466 25 2630190 2653813.53971931 3312351.16666667 0.801187255272192 0.99109826694086 26 2592882 2552913.27744046 3340166.875 0.764307105895857 1.01565612232610 27 3785309 3505327.87732478 3362423.33333333 1.04250046166845 1.07987301972131 28 3231539 3442462.8011857 3381469.125 1.01803762623020 0.938728807436046 29 3421369 3364224.02048927 3398526.04166667 0.98990679466426 1.01698608034504 30 3312134 3242128.23098087 3418444.54166667 0.948422064907969 1.02159253552965 31 4647303 4559833.64246677 3441166.75 1.32508360499147 1.01918257646915 32 4289177 4403881.15393444 3454586.08333333 1.27479270966238 0.973953848906216 33 3463853 3445604.08126988 3444025.45833333 1.00045836564092 1.00529629008432 34 3304422 3347232.68596527 3461659.66666667 0.96694447411938 0.987210125503144 35 3006121 3091666.99732059 3493081.125 0.885083079002521 0.972330138596838 36 3464238 3437851.76751073 3496322.66666667 0.983276457944404 1.00767520948362 37 2921118 2809108.73365839 3506182.5 0.801187255272192 1.03987359584893 38 2624018 2696161.84891813 3527589.66666667 0.764307105895857 0.973242018483764 39 3500718 3699142.35252999 3548336.41666667 1.04250046166845 0.946359362895488 40 3939351 3631722.95249234 3567375.95833333 1.01803762623020 1.08470581361294 41 3467672 3555968.76038515 3592225.83333333 0.98990679466426 0.975169421798974 42 3343628 3429070.99287834 3615553.79166667 0.948422064907969 0.975082757675246 43 4852445 4812207.18867167 3631625.33333333 1.32508360499147 1.00836161240585 44 4597807 4649943.13001164 3647607.25 1.27479270966238 0.988787791903273 45 3653145 3677248.91899166 3675564.16666667 1.00045836564092 0.993445121741101 46 3572079 3574501.01866916 3696697.29166667 0.96694447411938 0.99932241768669 47 3334861 3287361.44758036 3714184.04166667 0.885083079002521 1.01444914201771 48 3695369 3683654.61696542 3746306.125 0.983276457944404 1.00318009809623 49 3075704 3029261.47137226 3780965.625 0.801187255272192 1.01533130403785 50 2852998 2924496.04911416 3826336.33333333 0.764307105895857 0.975552010358905 51 3942704 4039541.38421226 3874858.125 1.04250046166845 0.97602762912871 52 4004560 3988385.60550634 3917719.25 1.01803762623020 1.0040553738012 53 3822145 3923531.83598815 3963536.625 0.98990679466426 0.974159293150577 54 3760085 3801691.79584970 4008438.79166667 0.948422064907969 0.989055715696069 55 5267816 5358022.48682734 4043535.41666667 1.32508360499147 0.983164220185877 56 5271333 5194689.09107909 4074928.45833333 1.27479270966238 1.014754282225 57 4144142 4126433.2986811 4124542.75 1.00045836564092 1.00429152734022 58 4109749 4022001.06798137 4159495.375 0.96694447411938 1.02181698376890 59 3896808 3703527.3638135 4184383.875 0.885083079002521 1.05218825654564 60 4211074 4147629.63285878 4218172.41666667 0.983276457944404 1.01529653627667 61 3402318 3393421.17534046 4235490.70833333 0.801187255272192 1.00262178615617 62 3279817 3252111.13098346 4254979.58333333 0.764307105895857 1.00851934878626 63 4706628 4450672.63878061 4269228.45833333 1.04250046166845 1.05750936588532 64 4079499 4342722.97574557 4265778.45833333 1.01803762623020 0.939387343559399 65 4344530 4205039.67417953 4247914.75 0.98990679466426 1.03317217829762 66 4048625 4003318.5023671 4221030.54166667 0.948422064907969 1.01131723534016 67 5394915 NA NA 1.32508360499147 NA 68 5611967 NA NA 1.27479270966238 NA 69 4145481 NA NA 1.00045836564092 NA 70 4025610 NA NA 0.96694447411938 NA 71 3552218 NA NA 0.885083079002521 NA 72 3910443 NA NA 0.983276457944404 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/1opcb1263303612.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/1opcb1263303612.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/2elqb1263303612.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/2elqb1263303612.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/3oou91263303612.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/3oou91263303612.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/4pi501263303612.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263303675z83buikdoeyv8et/4pi501263303612.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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