The CrossEntropy Method for EstimationD. P. Kroese, R. Y. Rubinstein, and P. W. Glynn To appear in Handbook of Statistics, Vol. 31, Eds. V. Govindaraju and C. R. Rao, Elsevier This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the crossentropy (CE) method. The CE method can be viewed as an adaptive importance sampling procedure that uses the crossentropy or Kullback–Leibler divergence as a measure of closeness between two sampling distributions. The CE method is particularly useful for the estimation of rareevent 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 CrossEntropy Method for Optimization”.
