Isbn: 9786130302238 - stochastic process: probability theory, deterministic system (mathematics), gillespie algorithm, markov chain, stochastic calculus, dynamics of markovian particles (2 risultati)

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    • Lingua: Inglese

      Editore: VDM Verlag Dr. Müller E.K. Dez 2009, 2009

      6130302231 / 9786130302238

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      EUR 29,00

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online.In probability theory, a stochastic process, or sometimes random process, is the counterpart to a deterministic process. Instead of dealing with only one possible 'reality' of how the process might evolve under time (as is the case, for example, for solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy in its future evolution described by probability distributions. This means that even if the initial condition (or starting point) is known, there are many possibilities the process might go to, but some paths are more probable and others less. Englisch.

    • Lingua: Inglese

      Editore: Omniscriptum, 2010

      6130302231 / 9786130302238

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      EUR 162,38

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      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online.In probability theory, a stochastic process, or sometimes random process, is the counterpart to a deterministic process. Instead of dealing with only one possible 'reality' of how the process might evolve under time (as is the case, for example, for solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy in its future evolution described by probability distributions. This means that even if the initial condition (or starting point) is known, there are many possibilities the process might go to, but some paths are more probable and others less.