Markov Chains: States Classification

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Probability & Stochastic Processes

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Sunny Rainy Source: Markov Model

Explores a first-order Markov model using a sunny-rainy source example, demonstrating how past events influence future outcomes.

Lindblad equation

Covers the interpretation of the Lindblad equation and its unitary part in quantum gases.

Numerical Analysis: Stability in ODEs

Covers the stability analysis of ODEs using numerical methods and discusses stability conditions.

Markov Chains: Ergodic Chains Examples

Covers stochastic models for communications, focusing on discrete-time Markov chains.

Markov Chains: Communicating Classes

Explores communicating classes in Markov chains, distinguishing between transient and recurrent classes, and delves into the properties of these classes.

Probability Inequalities

Explores probability inequalities, convergence types, and moment generating functions for distribution approximation.

Stochastic Models: Absorbing Markov Chains Examples

Covers examples of absorbing Markov chains in discrete time.

Bonus Malus System: Transition Probabilities

Explores the Bonus Malus system for insurance premiums and Markov chain transition probabilities.

Markov Chains: Recurrence and Transience

Explores first passage times, strong Markov property, and state recurrence/transience in Markov chains.