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Description
  • The paper recals the MCMC methods, namely the Gibbs algorithm, the Metropolis--Hastings algorithm and variants used for solution of optimization problems, namely the simulated annealing. The objective is to describe the schemes of the algorithms, to recall their theoretical foundation, and to show their use both in Bayes data analysis and in randomized optimization problem.
  • The paper recals the MCMC methods, namely the Gibbs algorithm, the Metropolis--Hastings algorithm and variants used for solution of optimization problems, namely the simulated annealing. The objective is to describe the schemes of the algorithms, to recall their theoretical foundation, and to show their use both in Bayes data analysis and in randomized optimization problem. (en)
Title
  • Markov Chain Monte Carlo methods in computational statistics and econometrics
  • Markov Chain Monte Carlo methods in computational statistics and econometrics (en)
skos:prefLabel
  • Markov Chain Monte Carlo methods in computational statistics and econometrics
  • Markov Chain Monte Carlo methods in computational statistics and econometrics (en)
skos:notation
  • RIV/67985556:_____/06:00041470!RIV10-AV0-67985556
http://linked.open...avai/riv/aktivita
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  • P(GA402/04/1294), Z(AV0Z10750506)
http://linked.open...vai/riv/dodaniDat
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  • 484235
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  • RIV/67985556:_____/06:00041470
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  • Random search; MCMC; optimization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [82E9747614FA]
http://linked.open...v/mistoKonaniAkce
  • Plzeň
http://linked.open...i/riv/mistoVydani
  • Plzeň
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  • Proceedings of the 24th International Conference Mathematical Methods in Economics 2006
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  • Volf, Petr
http://linked.open...vavai/riv/typAkce
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http://linked.open...n/vavai/riv/zamer
number of pages
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  • Západočeská univerzita v Plzni
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  • 978-80-7043-480-2
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