Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.
Covers the Metropolis-Hastings algorithm and gradient-based approaches for biasing searches towards higher likelihood values.
Introduces continuous time Markov chains on a finite state space with exponential waiting times and jump probabilities.
Explores the panel effect model with fixed and random effects, discussing estimation challenges and the impact of serial correlation.
