  Quasi-stationary distributions (QSD) have been widely studied since the
pioneering work of Kolmogorov (1938), Yaglom (1947) and Sevastyanov (1951).
They appear as a natural object when considering Markov processes that are
certainly absorbed since they are invariant for the evolution of the
distribution of the process conditioned on not being absorbed. They hence
appropriately describe the state of the process at large times for non absorbed
paths. Unlike invariant distributions for Markov processes, QSD are solutions
of a non-linear equation and there can be 0, 1 or an infinity of them. Also,
they cannot be obtained as Ces\`aro limits of Markovian dynamics. These facts
make the computation of QSDs a nontrivial matter. We review different
approximation methods for QSD that are useful for simulation purposes, mainly
focused on Fleming-Viot dynamics. We also give some alternative proofs and
extensions of known results.
