Invariant distribution: properties and examples

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Markov Chains: Ergodic Chains Examples

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

Discrete-Time Markov Chains: Definitions

Covers the definitions and state probabilities of discrete-time Markov chains.

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.

Markov Chains: Transition Probabilities

Explores Markov chains, transition matrices, distribution, and random walks.

Markov Chains and Applications

Explores Markov chains, their properties, and algorithmic applications, emphasizing information quantification and state monotonicity.

Invariant Distributions: Markov Chains

Explores invariant distributions, recurrent states, and convergence in Markov chains, including practical applications like PageRank in Google.

Markov Chains: Hitting Probabilities

Explores hitting probabilities in Markov chains, covering minimal solutions, proofs, and recursive relationships.

Discrete-Time Markov Chains: Definitions

Covers the definitions and state probabilities of discrete-time Markov chains.

Optimal Selling Strategy

Covers the optimal selling strategy in a dynamic scenario to maximize profit.