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Stochastic process
Details
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.
Klappentext
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.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786130302238
- Editor Lambert M. Surhone, Miriam T. Timpledon, Susan F. Marseken
- Sprache Englisch
- Größe H220mm x B220mm
- Jahr 2009
- EAN 9786130302238
- Format Fachbuch
- ISBN 978-613-0-30223-8
- Titel Stochastic process
- Untertitel Probability theory, Deterministic system (mathematics), Gillespie algorithm, Markov chain, Stochastic calculus, Dynamics of Markovian particles
- Herausgeber VDM Verlag Dr. Müller e.K.
- Anzahl Seiten 72
- Genre Mathematik