The Large Deviations of Bias Point Selection

  • James Antonio Bucklew
Part of the Springer Series in Statistics book series (SSS)


Suppose the inputs to the system are i.i.d. random variables {X i }, which have the scalar density function p(·). We are interested in \( \rho = P\left( {\sum\nolimits_{j = 1}^n {{X_i} > na} } \right)\). We simulate with i.i.d. {S i } whose individual density functions are q(·). In the light of Theorem 5.1.1, let us compute the variance rates for the input and output estimators, respectively.


Variance Rate Output Estimator Output Simulation Direct Monte Carlo Simulation Exponential Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • James Antonio Bucklew
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of Wisconsin-MadisonMadisonUSA

Personalised recommendations