classical deomposition -- eigen reeks -- additief

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 07 Jun 2009 14:36:21 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x.htm/, Retrieved Sun, 07 Jun 2009 22:37:08 +0200

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/Jun/07/t1244407024ghtdj2lxsxnpr5x.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 «

517 540 454 292 445 483 545 355 370 372 422 445 471 413 307 308 389 377 521 420 413 384 466 434 263 334 334 416 309 334 350 337 277 439 433 455 372 409 471 382 417 405 410 357 360 329 359 393 448 593 535 449 742 631 513 526 677 631 547 533 433 427 470 418 485 464 439 452 423 537 384 380

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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 517 NA NA -33.0097222222222 NA 2 540 NA NA 4.86527777777777 NA 3 454 NA NA -8.18472222222222 NA 4 292 NA NA -38.8013888888889 NA 5 445 NA NA 33.9402777777778 NA 6 483 NA NA 8.59861111111114 NA 7 545 471.390277777778 434.75 36.6402777777778 73.6097222222222 8 355 397.023611111111 427.541666666667 -30.5180555555556 -42.0236111111111 9 370 406.815277777778 416.125 -9.30972222222224 -36.8152777777777 10 372 411.773611111111 410.666666666667 1.10694444444443 -39.7736111111111 11 422 423.123611111111 409 14.1236111111111 -1.12361111111113 12 445 422.798611111111 402.25 20.5486111111111 22.2013888888889 13 471 363.823611111111 396.833333333333 -33.0097222222222 107.176388888889 14 413 403.406944444444 398.541666666667 4.86527777777777 9.59305555555557 15 307 394.856944444444 403.041666666667 -8.18472222222222 -87.8569444444445 16 308 366.531944444444 405.333333333333 -38.8013888888889 -58.5319444444444 17 389 441.606944444444 407.666666666667 33.9402777777778 -52.6069444444444 18 377 417.640277777778 409.041666666667 8.59861111111114 -40.6402777777778 19 521 436.556944444444 399.916666666667 36.6402777777778 84.4430555555555 20 420 357.440277777778 387.958333333333 -30.5180555555556 62.5597222222223 21 413 376.481944444444 385.791666666667 -9.30972222222224 36.5180555555555 22 384 392.523611111111 391.416666666667 1.10694444444443 -8.52361111111105 23 466 406.706944444445 392.583333333333 14.1236111111111 59.2930555555555 24 434 408.006944444444 387.458333333333 20.5486111111111 25.9930555555555 25 263 345.531944444444 378.541666666667 -33.0097222222222 -82.5319444444444 26 334 372.823611111111 367.958333333333 4.86527777777777 -38.8236111111111 27 334 350.648611111111 358.833333333333 -8.18472222222222 -16.6486111111111 28 416 316.656944444444 355.458333333333 -38.8013888888889 99.3430555555556 29 309 390.315277777778 356.375 33.9402777777778 -81.3152777777778 30 334 364.473611111111 355.875 8.59861111111114 -30.4736111111111 31 350 397.931944444444 361.291666666667 36.6402777777778 -47.9319444444444 32 337 338.440277777778 368.958333333333 -30.5180555555556 -1.44027777777779 33 277 368.481944444444 377.791666666667 -9.30972222222224 -91.4819444444444 34 439 383.190277777778 382.083333333333 1.10694444444443 55.8097222222223 35 433 399.290277777778 385.166666666667 14.1236111111111 33.7097222222223 36 455 413.173611111111 392.625 20.5486111111111 41.8263888888889 37 372 365.073611111111 398.083333333333 -33.0097222222222 6.92638888888894 38 409 406.281944444444 401.416666666667 4.86527777777777 2.71805555555562 39 471 397.523611111111 405.708333333333 -8.18472222222222 73.4763888888889 40 382 365.781944444444 404.583333333333 -38.8013888888889 16.2180555555556 41 417 430.856944444444 396.916666666667 33.9402777777778 -13.8569444444444 42 405 399.848611111111 391.25 8.59861111111114 5.1513888888889 43 410 428.473611111111 391.833333333333 36.6402777777778 -18.4736111111110 44 357 372.148611111111 402.666666666667 -30.5180555555556 -15.1486111111111 45 360 403.690277777778 413 -9.30972222222224 -43.6902777777777 46 329 419.565277777778 418.458333333333 1.10694444444443 -90.5652777777777 47 359 448.915277777778 434.791666666667 14.1236111111111 -89.9152777777778 48 393 478.298611111111 457.75 20.5486111111111 -85.2986111111112 49 448 438.448611111111 471.458333333333 -33.0097222222222 9.55138888888888 50 593 487.656944444444 482.791666666667 4.86527777777777 105.343055555556 51 535 494.856944444444 503.041666666667 -8.18472222222222 40.1430555555556 52 449 490.031944444444 528.833333333333 -38.8013888888889 -41.0319444444444 53 742 583.190277777778 549.25 33.9402777777778 158.809722222222 54 631 571.515277777778 562.916666666667 8.59861111111114 59.4847222222222 55 513 604.765277777778 568.125 36.6402777777778 -91.7652777777777 56 526 530.065277777778 560.583333333333 -30.5180555555556 -4.06527777777785 57 677 541.648611111111 550.958333333333 -9.30972222222224 135.351388888889 58 631 548.065277777778 546.958333333333 1.10694444444443 82.9347222222221 59 547 549.081944444444 534.958333333333 14.1236111111111 -2.08194444444439 60 533 537.840277777778 517.291666666667 20.5486111111111 -4.84027777777771 61 433 474.240277777778 507.25 -33.0097222222222 -41.2402777777777 62 427 505.948611111111 501.083333333333 4.86527777777777 -78.948611111111 63 470 479.231944444444 487.416666666667 -8.18472222222222 -9.23194444444437 64 418 434.115277777778 472.916666666667 -38.8013888888889 -16.1152777777777 65 485 496.148611111111 462.208333333333 33.9402777777778 -11.1486111111111 66 464 457.640277777778 449.041666666667 8.59861111111114 6.35972222222227 67 439 NA NA 36.6402777777778 NA 68 452 NA NA -30.5180555555556 NA 69 423 NA NA -9.30972222222224 NA 70 537 NA NA 1.10694444444443 NA 71 384 NA NA 14.1236111111111 NA 72 380 NA NA 20.5486111111111 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/1vkuc1244406979.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/1vkuc1244406979.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/2fumk1244406979.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/2fumk1244406979.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/32cpu1244406979.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/32cpu1244406979.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/4w03x1244406979.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244407024ghtdj2lxsxnpr5x/4w03x1244406979.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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