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» On the importance function in splitting simulation
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ETT
2002
77views Education» more  ETT 2002»
13 years 4 months 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, ...
VALUETOOLS
2006
ACM
13 years 10 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
13 years 10 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
13 years 5 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»
13 years 8 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