Original title: Model for Difference of Two Series of Poisson-like Count Data
Translated title: Model pro rozdíl dvou Poissonových veličin
Authors: Volf, Petr
Document type: Papers
Conference/Event: 26th International Conference Mathematical Methods in Economics 2008, Liberec (CZ), 2008-09-17 / 2008-09-19
Year: 2008
Language: eng
Abstract: [eng] [cze]
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. 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).
Keywords: count data; MCMC; Poisson distribution; Skellam distribution
Project no.: CEZ:AV0Z10750506 (CEP), GA402/07/1113 (CEP)
Funding provider: GA ČR
Host item entry: Proceedings of 26th International Conference Mathematical Methods in Economics 2008, ISBN 978-80-7372-387-3

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2008/SI/volf-model for difference of two series of poisson-like count data.pdf
Original record: http://hdl.handle.net/11104/0165395

Permalink: http://www.nusl.cz/ntk/nusl-39404


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers