Sampling, feasibility, and priors in data assimilation

DOI10.3934/dcds.2016.36.4227zbMath1333.65007arXiv1506.00043OpenAlexW2331600332MaRDI QIDQ262096

Robert N. Miller, Matthias Morzfeld, Xuemin Tu, Fei Lu, Alexandre Joel Chorin

Publication date: 29 March 2016

Published in: Discrete and Continuous Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1506.00043

zbMATH Keywords

Monte Carlomodel reductionBayesian estimationdata assimilation

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Complexity and performance of numerical algorithms (65Y20) Sequential estimation (62L12)

Related Items (8)

Stochastic resonance in a high-order time-delayed feedback tristable dynamic system and its application ⋮ ISALT: inference-based schemes adaptive to large time-stepping for locally Lipschitz ergodic systems ⋮ Stochastic resonance in an asymmetric bistable system driven by multiplicative and additive Gaussian noise and its application in bearing fault detection ⋮ Decreasing bit error rate by using enhanced tristable logical stochastic resonance in heavy noise condition ⋮ Iterative Importance Sampling Algorithms for Parameter Estimation ⋮ Downscaling data assimilation algorithm with applications to statistical solutions of the Navier-Stokes equations ⋮ Stochastic resonance in an asymmetric tristable system driven by correlated noises ⋮ Multi-parameter-adjusting stochastic resonance in a standard tri-stable system and its application in incipient fault diagnosis

Uses Software

• EnKF

Cites Work

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• Ensemble samplers with affine invariance
• Implicit estimation of ecological model parameters
• A random map implementation of implicit filters
• A contrast estimator for completely or partially observed hypoelliptic diffusion
• Implicit particle filters for data assimilation
• Bayesian inference with optimal maps
• Parameter estimation by implicit sampling
• Monte-Carlo technique in problems of optimal information processing
• A computational strategy for multiscale systems with applications to Lorenz 96 model
• Sequential Monte Carlo Methods in Practice
• Small-Noise Analysis and Symmetrization of Implicit Monte Carlo Samplers
• Inverse problems: A Bayesian perspective
• Parameter Estimation for Partially Observed Hypoelliptic Diffusions
• Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems
• Deterministic Nonperiodic Flow
• Rare Event Simulation of Small Noise Diffusions
• Blind Deconvolution via Sequential Imputations
• Stochastic Tools in Mathematics and Science
• Physics constrained nonlinear regression models for time series
• Estimating the uncertainty in underresolved nonlinear dynamics
• Linear theory for filtering nonlinear multiscale systems with model error
• Data Assimilation

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