Efficient Simulation of Large Deviation Events for Sums of Random Vectors Using Saddle-Point Representations
DOI10.1239/jap/1378401231zbMath1282.65025arXiv1203.0817OpenAlexW2074851174MaRDI QIDQ2854076
Ankush Agarwal, Sandeep Juneja, Santanu S. Dey
Publication date: 17 October 2013
Published in: Journal of Applied Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1203.0817
algorithmimportance samplingMonte Carlo methodlarge deviationsnumerical experimentrare event simulationsaddle-point approximationFourier inversionexponential twisting method
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Counterexamples in importance sampling for large deviations probabilities
- On Monte Carlo estimation of large deviations probabilities
- Introduction to rare event simulation.
- Stochastic simulation: Algorithms and analysis
- Importance Sampling for Portfolio Credit Risk
- Efficient Simulation of Light-Tailed Sums: an Old-Folk Song Sung to a Faster New Tune...
- Monte Carlo simulation and large deviations theory for uniformly recurrent Markov chains
- On large deviations theory and asymptotically efficient Monte Carlo estimation
- Saddlepoint Approximations with Applications
- A quick simulation method for excessive backlogs in networks of queues
- Saddle point approximation for the distribution of the sum of independent random variables
- Uniformly Efficient Importance Sampling for the Tail Distribution of Sums of Random Variables
- On asymptotically efficient simulation of large deviation probabilities
- Saddlepoint Approximations in Statistics
This page was built for publication: Efficient Simulation of Large Deviation Events for Sums of Random Vectors Using Saddle-Point Representations
