Explores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.
Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.
Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.
Explores equilibrium in Markov Chains, covering invariant distributions, properties determination, and practical applications.
Delves into the proof of the convergence rate theorem for an ergodic Markov chain, emphasizing eigenvalues and detailed balance properties.
