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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...
We investigate the question of when sampling a stochastic process X = {X(t): t≥0} at the times of an independent point process ψ leads to the same empirical distribution as the time-average limiting d...
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...
Capacity Value of Additional Generation: Probability Theory and Sampling Uncertainty
Power system planning Power system operation Power system reliability Risk analysis Wind energy
2013/6/17
The concept of capacity value is widely used to quantify the contribution of additional generation (most notably renewables) within generation adequacy assessments. This paper surveys the existing pro...
Estimating Network Degree Distributions Under Sampling: An Inverse Problem, with Applications to Monitoring Social Media Networks
Estimating Network Degree Distributions Sampling An Inverse Problem Applications Monitoring Social Media Networks
2013/6/14
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
An analysis of block sampling strategies in compressed sensing
Compressed Sensing blocks of measurements sampling continuous trajectories exact recovery,ℓ 1 minimization.
2013/6/17
Compressed sensing (CS) is a theory which guarantees the exact recovery of sparse signals from a few number of linear projections. The sampling schemes suggested by current CS theories are often of li...
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...
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Central limit theorems for pre-averaging covariance estimators under endogenous sampling times
Central limit theorem Hitting times Market microstructure noise Nonsynchronous observa-tions Pre-averaging Time endogeneity
2013/6/13
We consider two continuous It\^o semimartingales observed with noise and sampled at stopping times in a nonsynchronous manner. In this article we establish a central limit theorem for the pre-averaged...
Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference
Generalized Thompson Sampling Sequential Decision-Making Causal Inference
2013/5/2
Recently, it has been shown how sampling actions from the predictive distribution over the optimal action-sometimes called Thompson sampling-can be applied to solve sequential adaptive control problem...