Introduction to stochastic processes with applications to biology /
Material type: TextPublication details: Boca Raton, FL : Chapman & Hall/CRC, c2011Edition: 2nd edDescription: xxiv, 466 p. : illISBN: 9781439818824 (hardback); 1439818827 (hardback)Subject(s): Stochastic processes | BiomathematicsDDC classification: 519.23 Summary: "The second edition of a bestseller, this textbook delineates stochastic processes, emphasizing applications in biology. It includes MATLAB throughout the book to help with the solutions of various problems. The book is organized according to the three types of stochastic processes: discrete time Markov chains, continuous time Markov chains and continuous time and state Markov processes. It contains a new chapter on the biological applications of stochastic differential equations and new sections on alternative methods for derivation of a stochastic differential equation, data and parameter estimation, Monte Carlo simulation, and more"--Item type | Current library | Collection | Call number | Status | Date due | Barcode |
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BK | Kannur University Central Library Stack | Stack | 519.23 ALL/I (Browse shelf (Opens below)) | Available | 31716 |
Browsing Kannur University Central Library shelves, Shelving location: Stack, Collection: Stack Close shelf browser (Hides shelf browser)
519.2 VEN/T Theory of probability : explorations and applications | 519.2 WOO/E Everyday probablity and statistics: Health, elections, gambling and war | 519.20113 BAR/P Probability and Statistics for Computer Scientists. | 519.23 ALL/I Introduction to stochastic processes with applications to biology / | 519.23 MCI/S Stochastic interest rate | 519.23 OLO/P Probability, statistics, and stochastic processes | 519.232 BAS/S Stochastic processes |
"The second edition of a bestseller, this textbook delineates stochastic processes, emphasizing applications in biology. It includes MATLAB throughout the book to help with the solutions of various problems. The book is organized according to the three types of stochastic processes: discrete time Markov chains, continuous time Markov chains and continuous time and state Markov processes. It contains a new chapter on the biological applications of stochastic differential equations and new sections on alternative methods for derivation of a stochastic differential equation, data and parameter estimation, Monte Carlo simulation, and more"--
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