Iterative Importance Sampling Algorithms for Parameter Estimation
Iterative Importance Sampling Algorithms for Parameter Estimation
In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect …