Results 41 to 50 of about 2,675,626 (288)
Approximate Methods for Maximum Likelihood Estimation of Multivariate Nonlinear Mixed-Effects Models
Entropy, 2015 Multivariate nonlinear mixed-effects models (MNLMM) have received increasing use due to their flexibility for analyzing multi-outcome longitudinal data following possibly nonlinear profiles.
Wan-Lun Wang
doaj +1 more source
Mechanical Engineering Journal, 2023 The significance of probabilistic risk assessments (PRAs) of nuclear power plants against external events was re-recognized after the Fukushima Daiichi Nuclear Power Plant accident.
Kotaro KUBO +5 more
doaj +1 more source
Stochastic Optimization with Importance Sampling [PDF]
, 2015 Uniform sampling of training data has been commonly used in traditional stochastic optimization algorithms such as Proximal Stochastic Gradient Descent (prox-SGD) and Proximal Stochastic Dual Coordinate Ascent (prox-SDCA).
Zhang, Tong, Zhao, Peilin
core
Selection of proposal distributions for generalized importance sampling estimators [PDF]
, 2019 The standard importance sampling (IS) estimator, generally does not work well in examples involving simultaneous inference on several targets as the importance weights can take arbitrarily large values making the estimator highly unstable.
Evangelou, Evangelos, Roy, Vivekananda
core +2 more sources
, 2005 There arise two problems when the expectation of some function with respect to a nonuniform multivariate distribution has to be computed by (quasi-) Monte Carlo integration: the integrand can have singularities when the domain of the distribution is unbounded and it can be very expensive or even impossible to sample points from a general multivariate ...
Hörmann, Wolfgang, Leydold, Josef
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source
Robust Covariance Adaptation in Adaptive Importance Sampling
, 2018 Importance sampling (IS) is a Monte Carlo methodology that allows for approximation of a target distribution using weighted samples generated from another proposal distribution.
Bugallo, Monica F. +2 more
core +1 more source
Rare event simulation via importance sampling for linear SPDE's [PDF]
, 2017 The goal of this paper is to develop provably efficient importance sampling Monte Carlo methods for the estimation of rare events within the class of linear stochastic partial differential equations (SPDEs).
Salins, Michael +1 more
core +2 more sources
Neural Importance Sampling [PDF]
ACM Transactions on Graphics, 2019 We propose to use deep neural networks for generating samples in Monte Carlo integration. Our work is based on non-linear independent components estimation (NICE), which we extend in numerous ways to improve performance and enable its application to integration problems.
Thomas Müller +4 more
openaire +2 more sources
Treatment Decision‐Making Roles and Preferences Among Adolescents and Young Adults With Cancer
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Decision‐making (DM) dynamics between adolescents and young adults (AYAs) with cancer, parents, and oncologists remain underexplored in diverse populations. We examined cancer treatment DM preferences among an ethnically and socioeconomically diverse group of AYAs and their parents.
Amanda M. Gutierrez +14 more
wiley +1 more source