Title :
Universal simulation distributions
Author :
Bucklew, James A. ; Nitinawarat, Sirin ; Wierer, Jay
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA
Abstract :
In this paper, we present a new class of importance sampling simulation distributions, the universal distributions. We show that these distributions are universally efficient in the sense that they depend only on a single scalar parameter regardless of the dimensionality of the underlying system or of the error sets to be simulated.
Keywords :
importance sampling; probability; Monte Carlo simulation; importance sampling; large deviation theory; scalar parameter; universal simulation distributions; Books; Communication systems; Discrete event simulation; H infinity control; Monte Carlo methods; Probability density function; Random number generation; Random variables; Sampling methods; Signal detection; Importance sampling; Monte Carlo simulation; large deviation theory;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2004.836875
