搜索结果: 1-15 共查到“Importance sampling”相关记录19条 . 查询时间(0.109 秒)
Optimal mixture weights in multiple importance sampling
multiple importance sampling mixture
2015/8/21
In multiple importance sampling we combine samples from a nite list
of proposal distributions. When those proposal distributions are used to
create control variates, it is possible (Owen and Zhou, ...
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...
Examples comparing Importance Sampling and the Metropolis algorithm
Sampling order markov chain monte carlo simulation technology the markov chain
2015/7/8
Importance sampling, particularly sequential and adaptive importance sampling, have emerged as competitive simulation techniques to Markov–chain Monte–Carlo techniques. We compare importance sampling ...
A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES
Sequential sampling algorithms the random graph degree
2015/7/8
A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES。
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...
State-independent importance sampling for regularly varying random walks
State-independent regularly random walks
2012/9/14
Efficient simulation of rare events involving sums of heavy-tailed random vari-ables has been an active research area in applied probability in the lastfifteen years.These rare events arise in many ap...
Interval importance sampling method for finite element-based structural reliability assessment under parameter uncertainties
Finite element method Importance sampling Imprecise probability Interval analysis Interval uncertainty Probability box Simulation Structural reliability Statistical uncertainty
2012/4/26
Parameters of a probabilistic model often cannot be determined precisely on the basis of limited data. In this case the unknown parameters can be introduced as intervals, and the imprecise probability...
Importance Sampling for Multiscale Diffusions
importance sampling Monte Carlo homogenization multiscale rough energy landscape
2011/9/21
Abstract: We construct importance sampling schemes for stochastic differential equations with small noise and fast oscillating coefficients. Standard Monte Carlo methods perform poorly for these probl...
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...