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  • V článku jsou popsány dvě metody analýzy časových řad bootstrapovou metodou,autoregresní model prvního řádu a model klouzavých bloků.Obě metody jsou demonstrovány i na praktických příkladech.Výsledky obou metod jsou v závěru článku porovnány. (cs)
  • Many probabilistic models are used to analyse the time series. Two different methods for bootstrapping time series are described in the paper. The simplest model ? a first order autoregressive scheme is described and presented in the practical example. The principle of this method is fitting a model and then sampling from the residuals. The different presented method is called the moving block bootstrap. An important advantage of the method is that is less ?model dependent? than the bootstrapping of residuals approach. The method is dependent on the model that is fit to the original time series. Results of both methods are compared in the paper. The methods for bootstrapping analogous to the solution for the regression models can be used and they are mentioned in the end.
  • Many probabilistic models are used to analyse the time series. Two different methods for bootstrapping time series are described in the paper. The simplest model ? a first order autoregressive scheme is described and presented in the practical example. The principle of this method is fitting a model and then sampling from the residuals. The different presented method is called the moving block bootstrap. An important advantage of the method is that is less ?model dependent? than the bootstrapping of residuals approach. The method is dependent on the model that is fit to the original time series. Results of both methods are compared in the paper. The methods for bootstrapping analogous to the solution for the regression models can be used and they are mentioned in the end. (en)
Title
  • RE-SAMPLING ESTIMATION IN TIME SERIES
  • RE-SAMPLING ESTIMATION IN TIME SERIES (en)
  • RE-SAMPLING ESTIMATION IN TIME SERIES (cs)
skos:prefLabel
  • RE-SAMPLING ESTIMATION IN TIME SERIES
  • RE-SAMPLING ESTIMATION IN TIME SERIES (en)
  • RE-SAMPLING ESTIMATION IN TIME SERIES (cs)
skos:notation
  • RIV/00216275:25410/07:00005479!RIV08-MSM-25410___
http://linked.open.../vavai/riv/strany
  • 145
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 447461
http://linked.open...ai/riv/idVysledku
  • RIV/00216275:25410/07:00005479
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • time series; first order autoregressive scheme; moving block bootstrap (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D6462223B7A7]
http://linked.open...v/mistoKonaniAkce
  • Ponta Delgada
http://linked.open...i/riv/mistoVydani
  • Azores, Portugal
http://linked.open...i/riv/nazevZdroje
  • ISBIS 2007
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kubanová, Jana
  • Linda, Bohdan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • University of Azores
https://schema.org/isbn
  • 978-989-95489-0-9
http://localhost/t...ganizacniJednotka
  • 25410
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