conditional maximum likelihood methods are considered for the parameter estimation of the model. Moreover, simulation experiments …

Likelihood based inference for multi-state latent factor intensity models is hindered by the fact that exact closed … dynamic econometric models. This paper reviews, adapts and compares three different approaches for solving this problem. For …

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …

comparison is based on a small simulation study. The processes that are simulated are in the class of ARMA (5,5) processes. Based … on the simulation evidence, we suggest to use a slightly modified version of Buehlmann's (1996) iterative method …. -- window width ; bandwidth ; non-parametric spectral estimation ; simulation …

Simulated models suffer intrinsically from validation and comparison problems. The choice of a suitable indicator … between alternative models is still an open problem calling for further investigation, especially in light of the increasing … models' synthetic output replicates the properties of observable time series without the need to resort to any likelihood …