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» On the importance function in splitting simulation
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98
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ETT
2002
77views Education» more  ETT 2002»
15 years 4 days ago
On the importance function in splitting simulation
The splitting method is a simulation technique for the estimation of very small probabilities. In this technique, the sample paths are split into multiple copies, at various stages...
Marnix J. J. Garvels, Jan-Kees C. W. van Ommeren, ...
96
Voted
VALUETOOLS
2006
ACM
15 years 6 months ago
Splitting with weight windows to control the likelihood ratio in importance sampling
Importance sampling (IS) is the most widely used efficiency improvement method for rare-event simulation. When estimating the probability of a rare event, the IS estimator is the ...
Pierre L'Ecuyer, Bruno Tuffin
AI
2007
Springer
15 years 6 months ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel
WSC
2004
15 years 1 months ago
Function-Approximation-Based Importance Sampling for Pricing American Options
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Nomesh Bolia, Sandeep Juneja, Paul Glasserman
ICANNGA
2007
Springer
100views Algorithms» more  ICANNGA 2007»
15 years 4 months ago
Softening Splits in Decision Trees Using Simulated Annealing
Predictions computed by a classification tree are usually constant on axis-parallel hyperrectangles corresponding to the leaves and have strict jumps on their boundaries. The densi...
Jakub Dvorák, Petr Savický