5 papers
Randomized Quasi-Monte Carlo and Importance Sampling for Super-Fast Growing Functions with Applications to Finance
Jianlong Chen, Yu Xu, Jiarui Du +1
Many problems can be formulated as high-dimensional integrals of discontinuous functions that exhibit significant boundary growth, challenging the error analysis and applications o…
Enhanced convergence rates of Adaptive Importance Sampling with recycling schemes via quasi-Monte Carlo methods
Jianlong Chen, Jiarui Du, Xiaoqun Wang +1
This article investigates the integration of quasi-Monte Carlo (QMC) methods using the Adaptive Multiple Importance Sampling (AMIS). Traditional Importance Sampling (IS) often suff…
Quasi-Monte Carlo and importance sampling methods for Bayesian inverse problems
Zhijian He, Hejin Wang, Xiaoqun Wang
Importance Sampling (IS), an effective variance reduction strategy in Monte Carlo (MC) simulation, is frequently utilized for Bayesian inference and other statistical challenges. Q…
Quasi-Monte Carlo for unbounded integrands with importance sampling
Du Ouyang, Xiaoqun Wang, Zhijian He
We consider the problem of estimating an expectation by quasi-Monte Carlo (QMC) methods, where is an unbounded smooth function on $ \mathbb{R}…
On the convergence conditions of Laplace importance sampling with randomized quasi-Monte Carlo
Zhan Zheng, Hejin Wang, Xiaoqun Wang
The study further explores randomized QMC (RQMC), which maintains the QMC convergence rate and facilitates computational efficiency analysis. Emphasis is laid on integrating random…