Mastering Stochastic Processes: A Guide to "Markov Chains" by J.R. Norris
The textbook is structured to move logically from foundational theory to advanced applications. Key Coverage
Martingales, potential theory, and an introduction to Brownian motion. Practical Applications
: Systems are often represented using state transition diagrams, where nodes are states and arrows indicate the probability of moving from one to another. Key Topics in the Norris Curriculum
: A frog hopping on lily pads. Its next jump depends only on which pad it is currently standing on, not how it arrived there.
Invariant distributions, time reversal, and the Ergodic Theorem for long-run averages.
Norris emphasizes that Markov chains are not just theoretical; they are powerful tools for modeling real-world phenomena: Markov Chains - Cambridge University Press & Assessment
Q-matrices, Poisson processes, birth-death processes, and forward/backward equations.
Mastering Stochastic Processes: A Guide to "Markov Chains" by J.R. Norris
The textbook is structured to move logically from foundational theory to advanced applications. Key Coverage
Martingales, potential theory, and an introduction to Brownian motion. Practical Applications
: Systems are often represented using state transition diagrams, where nodes are states and arrows indicate the probability of moving from one to another. Key Topics in the Norris Curriculum
: A frog hopping on lily pads. Its next jump depends only on which pad it is currently standing on, not how it arrived there.
Invariant distributions, time reversal, and the Ergodic Theorem for long-run averages.
Norris emphasizes that Markov chains are not just theoretical; they are powerful tools for modeling real-world phenomena: Markov Chains - Cambridge University Press & Assessment
Q-matrices, Poisson processes, birth-death processes, and forward/backward equations.