Covers the theory of Markov Chain Monte Carlo (MCMC) sampling and discusses convergence conditions, transition matrix choice, and target distribution evolution.
Covers modeling temporal dependence in time series, including trend, periodic components, regression, stationarity, autocorrelation, and independence testing.
