. Here, the focus shifts from "where do we go next?" to "how long do we stay here?" This allows for the modeling of real-world phenomena like radioactive decay, queueing at a bank, or the spread of an epidemic. Why It Matters By focusing on the geometry of the state space and the behavior of long-term averages (The Ergodic Theorem), Norris provides the tools to quantify randomness. Whether it’s MCMC (Markov Chain Monte Carlo) methods in modern AI or simple branching processes in biology, the "Norris approach" remains the definitive map for navigating uncertain systems. Would you like to dive deeper into a specific application, such as
One of the highlights of the text is the treatment of long-run behavior. Norris provides detailed proofs and explanations for: norris markov chains