A self-organizing state space model and simplex initial distribution search

This paper proposes a method to seek initial distributions of parameters for a self-organizing state space model proposed by Kitagawa (J Am Stat Assoc 93:1203–1215, 1998). Our method is based on the simplex Nelder–Mead algorithm for solving nonlinear and discontinuous optimization problems. We show the effectiveness of our method by applying it to a linear Gaussian model, a linear non-Gaussian model, a nonlinear Gaussian model, and a stochastic volatility model.