Approaching the parameter estimation quality of maximum likelihood via   generalized moments
  A simple criterion is presented for a practical construction of generalized moments that allow one to approach the theoretical Rao-Cramer limit for parameter estimation while avoiding the complexity of the maximum likelihood method in the cases of complicated probability distributions and/or very large event samples. 
Fyodor V. Tkachov (INR RAS, Moscow)