Markov Chains: Applications and Coupled Chains

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Coq: Introduction

Introduces Coq, covering defining propositions, proving theorems, and using tactics.

Markov Chains and Algorithm Applications

Covers the application of Markov chains and algorithms for function optimization and graph colorings.

Markov Chains: Recurrence and Transience

Explores recurrence, transience, and invariant distributions in Markov chains with proofs and examples.

The Languages of Isabelle: Isar, ML, and Scala

Explores the languages of Isabelle, focusing on Isar, ML, and Scala, covering proof schemes, Natural Deduction rules, inductive definitions, and the LCF approach.

Markov Chains Decomposition

Covers Markov chains decomposition, LLN proof, Inventory Model application, and average costs.

Continuous Time Markov Chains

Covers the basic theory for continuous time Markov chains and discusses communication, hitting probabilities, recurrence, and transience.

Markov Chains: Introduction and Properties

Covers the introduction and properties of Markov chains, including transition matrices and stochastic processes.

Birth and Death Chains

Explores transience and recurrence in Markov chains, emphasizing birth and death chains and random walks.

Markov Chains: Convergence and Equilibrium

Explores the convergence properties of Markov chains and the computation of long-run mean rewards.

MCMC Examples and Error Estimation

Covers Markov Chain Monte Carlo examples and error estimation methods.