Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …

Algorithms, Gibbs Sampling and Metropolis-Hastings Algorithm. Network and security risk management application focus is on how …

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …

based on efficient importance sampling (EIS) is detailed. Monte Carlo experiments, based on widely used diffusion processes …, evaluate its performance against an alternative importance sampling (IS) strategy, showing that EIS is at least equivalent, if …

This paper provides high-dimensional and flexible importance sampling procedures for the likelihood evaluation of …-modal target densities. Our approach is based upon the efficient importance sampling (EIS) approach of Richard and Zhang (2007) and … exploits the mixture structure of the model when constructing importance sampling distributions as mixture of distributions …

This paper provides high-dimensional and flexible importance sampling procedures for the likelihood evaluation of …-modal target densities. Our approach is based upon the efficient importance sampling (EIS) approach of Richard and Zhang (2007) and … exploits the mixture structure of the model when constructing importance sampling distributions as mixture of distributions …

refer to our new method as numerically accelerated importance sampling. The method is computationally and numerically …-off encountered by other sampling methods. An elaborate simulation study and an empirical application for U.S. stock returns reveal …