## The Cross-Entropy Method for Estimation
This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the cross-entropy (CE) method. The CE method can be viewed as an adaptive importance sampling procedure that uses the cross-entropy or Kullback-Leibler divergence as a measure of closeness between two sampling distributions. The CE method is particularly useful for the estimation of rare-event probabilities. The method can also be used to solve a diverse range of optimization problems. The optimization setting is described in detail in the chapter entitled “The Cross-Entropy Method for Optimization”. |