搜索结果: 1-12 共查到“管理学 importance sampling”相关记录12条 . 查询时间(0.107 秒)
Adaptive Importance Sampling via Stochastic Convex Programming
Adaptive Importance Sampling via Stochastic Convex Programming
2015/7/8
We show that the variance of the Monte Carlo estimator that is importance sampled from an exponential family is a convex function of the natural parameter of the distribution. With this insight, we pr...
Importance Sampling for Monte Carlo Estimation of Quantiles
quantiles importance sampling large deviations.
2015/7/8
This paper is concerned with applying importance sampling as a variance reduction tool for computing extreme quantiles. A central limit theorem is derived for each of four proposed importance sampling...
Importance Sampling Using the Semi-Regenerative Method
Importance Sampling Semi-Regenerative Method
2015/7/8
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate the expected cumulative reward until hitting a fixed set of states for a discrete-time Markov chain o...
Fluid Heuristics, Lyapunov Bounds, and Efficient Importance Sampling for a Heavy-tailed G/G/1 Queue
State-dependent importance sampling Rare-event simulation Heavy-tails
2015/7/6
We develop a strongly efficient rare-event simulation algorithm for computing the tail of the steady-state waiting time in a single server queue with regularly varying service times. Our algorithm is ...
Zero-Variance Importance Sampling Estimators for Markov Process Expectations
Importance sampling Markov process simulation
2015/7/6
We consider the use of importance sampling to compute expectations of functionals of Markov processes. For a class of expectations that can be characterized as positive solutions to a linear system, w...
On Lyapunov Inequalities and Subsolutions for Efficient Importance Sampling
Lyapunov Inequalities Efficient Importance Sampling
2015/7/6
In this article we explain some connections between Lyapunov methods and subsolutions of an associated Isaacs equation for the design of efficient importance sampling schemes. As we shall see, subsolu...
Penalized importance sampling for parameter estimation in stochastic differential equations
Chronic wasting disease Euler-Maruyama scheme Maximum likelihood estimation Partially observed discrete sparse data Penalized importance sampling Stochastic di
2013/6/14
We consider the problem of estimating parameters of stochastic differential equations with discrete-time observations that are either completely or partially observed. The transition density between t...
Metamodel-based importance sampling for structural reliability analysis
reliability analysis importance sampling metamodeling error kriging random fields active learning rare events
2011/6/16
Structural reliability methods aim at computing the probability of failure of systems with
respect to some prescribed performance functions. In modern engineering such functions
usually resort to ru...
Quantile estimation with adaptive importance sampling
Quantile estimation law of iterated logarithm adaptive im-portance sampling stochastic approximation Robbins–Monro
2010/3/11
We introduce new quantile estimators with adaptive importance
sampling. The adaptive estimators are based on weighted samples
that are neither independent nor identically distributed. Using a
new l...
Case-deletion importance sampling estimators: Central limit theorems and related results
Infinite Variance Influence Leverage Marginal Residual Sum of Squares Markov Chain Monte Carlo Model Averaging Moment Index Tail Behavior
2009/9/16
Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally ...
Estimation of cosmological parameters using adaptive importance sampling
Estimation cosmological parameters adaptive importance sampling
2010/3/19
We present a Bayesian sampling algorithm called adaptive importance sampling or Population
Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to consi...
Least Squares Importance Sampling for Monte Carlo Security Pricing
Monte Carlo Simulations Variance Reduction Techniques Importance Sampling Derivatives Pricing
2010/4/27
We describe a simple Importance Sampling strategy for Monte Carlo simulations based on a least
squares optimization procedure. With several numerical examples, we show that such Least Squares Importa...