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  • Při používání Poissonova rozdělení pravděpodobnosti často narážíme na problém jeho malé flexibility. Shrneme postupy, jak vhodně tuto distribuci modifikovat. Další možnost nabízejí situace, kdy analyzujeme rozdíl dvou Poissonovských veličin. Pro tento případ bylo odvozeno Skellamovo rozdělení. Ukážeme metodu statistické analýzy v tomto případě. Model zahrnuje latentní proměnné, proto je k analýze použito procedur MCMC (Markov Chain Monte Carlo). (cs)
  • When the discrete count data are analyzed, we are often facing the problems with insufficient flexibility of Poisson distribution. However, in many instances the variable of the interest is the difference of two count variables. For these cases, so called Skellam distribution is available, derived originally as the difference of two correlated Poissons. The model contains latent variables, which leads quite naturally to the use of Bayes approach and to data augmentation via the Markov Chain Monte Carlo generation.
  • When the discrete count data are analyzed, we are often facing the problems with insufficient flexibility of Poisson distribution. However, in many instances the variable of the interest is the difference of two count variables. For these cases, so called Skellam distribution is available, derived originally as the difference of two correlated Poissons. The model contains latent variables, which leads quite naturally to the use of Bayes approach and to data augmentation via the Markov Chain Monte Carlo generation. (en)
Title
  • Model for Difference of Two Series of Poisson-like Count Data
  • Model pro rozdíl dvou Poissonových veličin (cs)
  • Model for Difference of Two Series of Poisson-like Count Data (en)
skos:prefLabel
  • Model for Difference of Two Series of Poisson-like Count Data
  • Model pro rozdíl dvou Poissonových veličin (cs)
  • Model for Difference of Two Series of Poisson-like Count Data (en)
skos:notation
  • RIV/67985556:_____/08:00315077!RIV09-GA0-67985556
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA402/07/1113), Z(AV0Z10750506)
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
  • 379788
http://linked.open...ai/riv/idVysledku
  • RIV/67985556:_____/08:00315077
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Poisson distribution; count data; Skellam distribution; MCMC (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1C75FEBA4C59]
http://linked.open...v/mistoKonaniAkce
  • Liberec
http://linked.open...i/riv/mistoVydani
  • Liberec
http://linked.open...i/riv/nazevZdroje
  • Proceedings of 26th International Conference Mathematical Methods in Economics 2008
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Volf, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000260962300062
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Technická univerzita v Liberci
https://schema.org/isbn
  • 978-80-7372-387-3
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