Search
Search Results
-
Numerical Stochastic Model of Non-stationary Time Series of the Wind Chill Index
A numerical stochastic model of the high-resolution time series of the wind chill index is considered. The model is constructed under the assumption...
-
Sampling from Non-smooth Distributions Through Langevin Diffusion
In this paper, we propose proximal splitting-type algorithms for sampling from distributions whose densities are not necessarily smooth nor...
-
Weak Error for Nested Multilevel Monte Carlo
This article discusses MLMC estimators with and without weights, applied to nested expectations of the form E f ( E F ( Y , Z )| Y ). More precisely, we are...
-
First-Order Weak Balanced Schemes for Stochastic Differential Equations
We address the numerical solution of stochastic differential equations with multiplicative noise (SDEs) by means of balanced schemes. In particular,...
-
A comparison of Monte Carlo methods for computing marginal likelihoods of item response theory models
Nowadays, Bayesian methods are routinely used for estimating parameters of item response theory (IRT) models. However, the marginal likelihoods are...
-
On the Convergence Time of Some Non-Reversible Markov Chain Monte Carlo Methods
It is commonly admitted that non-reversible Markov chain Monte Carlo (MCMC) algorithms usually yield more accurate MCMC estimators than their...
-
A method for high-dimensional smoothing
We consider the problem of the computation of smoothed additive functional, which are some integrals with respect to the joint smoothing...
-
Linear Stochastic Fluid Networks: Rare-Event Simulation and Markov Modulation
We consider a linear stochastic fluid network under Markov modulation, with a focus on the probability that the joint storage level attains a value...
-
Type I Error Probability Spending for Post-Market Drug and Vaccine Safety Surveillance With Poisson Data
Statistical sequential hypothesis testing is meant to analyze cumulative data accruing in time. The methods can be divided in two types, group and...
-
Stochastic Enumeration with Importance Sampling
Many hard problems in the computational sciences are equivalent to counting the leaves of a decision tree, or, more generally, by summing a cost...
-
Location-invariant reduced-bias tail index estimation under a third-order framework
Under a convenient third-order framework, the asymptotic distributional behavior of a class of location-invariant reduced-bias tail index estimators...
-
Uncertainty Quantification of Stochastic Simulation for Black-box Computer Experiments
Stochastic simulations applied to black-box computer experiments are becoming more widely used to evaluate the reliability of systems. Yet, the...
-
Nonparametric dynamic state space modeling of observed circular time series with circular latent states: A Bayesian perspective
Circular time series have received relatively little attention in statistics, and modeling complex circular time series using the state space...
-
Tail Approximations for Sums of Dependent Regularly Varying Random Variables Under Archimedean Copula Models
In this paper, we compare two numerical methods for approximating the probability that the sum of dependent regularly varying random variables...
-
An Efficient Algorithm for Simulating the Drawdown Stop** Time and the Running Maximum of a Brownian Motion
We define the drawdown stop** time of a Brownian motion as the first time its drawdown reaches a duration of length 1. In this paper, we propose an...
-
Efficient Simulation for Dependent Rare Events with Applications to Extremes
We consider the general problem of estimating probabilities which arise as a union of dependent events. We propose a flexible series of estimators...
-
An oracle inequality for quasi-Bayesian nonnegative matrix factorization
The aim of this paper is to provide some theoretical understanding of quasi-Bayesian aggregation methods of nonnegative matrix factorization. We...
-
Coupling Importance Sampling and Multilevel Monte Carlo using Sample Average Approximation
In this work, we propose a smart idea to couple importance sampling and Multilevel Monte Carlo (MLMC). We advocate a per level approach with as many...
-
Walk On Spheres Algorithm for Helmholtz and Yukawa Equations via Duffin Correspondence
We show that a constant-potential time-independent Schrödinger equation with Dirichlet boundary data can be reformulated as a Laplace equation with...
-
An Algorithm for Approximating the Second Moment of the Normalizing Constant Estimate from a Particle Filter
We propose a new algorithm for approximating the non-asymptotic second moment of the marginal likelihood estimate, or normalizing constant, provided...