Results 71 to 80 of about 151,127 (170)

Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference.

PLoS ONE, 2020
An important feature of Bayesian statistics is the opportunity to do sequential inference: the posterior distribution obtained after seeing a dataset can be used as prior for a second inference.
Bram Thijssen, Lodewyk F A Wessels
doaj   +1 more source

Energy-Adaptive SGHSMC: A Particle-Efficient Nonlinear Filter for High-Maneuver Target Tracking

Mathematics
Tracking targets with nonlinear motion patterns remains a significant challenge in state estimation. We propose an energy-adaptive stochastic gradient Hamiltonian sequential Monte Carlo (SGHSMC) filter that combines adaptive energy dynamics with ...
Chang Ho Kang, Sun Young Kim
doaj   +1 more source

Bootstrapping Sequential Monte Carlo Tracking [PDF]

, 2003
Sequential Monte Carlo (SMC) methods have in recent years been applied to handle some of the problems inherent to model-based tracking. In this paper we suggest to apply bootstrapping to reduce the required number of particles in SMC tracking. By bootstrapping is meant to track reliable low-level image features and use them to bootstrap the high-level ...
Thomas B. Moeslund, Erik Granum
openaire   +1 more source

Monte Carlo Methods for Rough Free Energy Landscapes: Population Annealing and Parallel Tempering

, 2011
Parallel tempering and population annealing are both effective methods for simulating equilibrium systems with rough free energy landscapes. Parallel tempering, also known as replica exchange Monte Carlo, is a Markov chain Monte Carlo method while ...
A. Schug, C. Geyer, D.J. Earl, E. Bittner, G. Burgio, H.G. Katzgraber, J. Machta, J. Machta, J. Machta, J.B. Anderson, K. Hukushima, K. Hukushima, P. Grassberger, P. Laarhoven van, R. S. Ellis, R.A. Banos, R.H. Swendsen, S. Kirkpatrick, S. Trebst, U.H.E. Hansmann, W. Nadler, Y. Okamoto   +21 more
core   +1 more source

Estimating Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood [PDF]

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernández-Villaverde and Rubio-Ramírez (2004) and the Kalman filter.
Jesus Fernandez-Villaverde, Juan F. Rubio-Ramirez   +1 more
core   +3 more sources

On the efficient Monte Carlo implementation of path integrals

, 2004
We demonstrate that the Levy-Ciesielski implementation of Lie-Trotter products enjoys several properties that make it extremely suitable for path-integral Monte Carlo simulations: fast computation of paths, fast Monte Carlo sampling, and the ability to ...
B. Simon, C. J. Geyer, Cristian Predescu, H. P. McKean, Jr., M. Kalos, M. Kaç, R. P. Feynman, S. Kwapien, S. Mallat   +8 more
core   +1 more source

Asynchronous Anytime Sequential Monte Carlo

, 2014
We introduce a new sequential Monte Carlo algorithm we call the particle cascade. The particle cascade is an asynchronous, anytime alternative to traditional particle filtering algorithms. It uses no barrier synchronizations which leads to improved particle throughput and memory efficiency.
Brooks Paige, Frank D. Wood, Arnaud Doucet, Yee Whye Teh   +3 more
openaire   +3 more sources

Reliability Assessment of Power Systems with Photovoltaic Power Stations Based on Intelligent State Space Reduction and Pseudo-Sequential Monte Carlo Simulation

Energies, 2018
As the number and capacity of photovoltaic (PV) power stations increase, it is of great significance to evaluate the PV-connected power systems in an effective, reasonable, and quick way.
Wenxia Liu, Dapeng Guo, Yahui Xu, Rui Cheng, Zhiqiang Wang, Yueqiao Li   +5 more
doaj   +1 more source

Quickest attack detection in smart grid based on sequential Monte Carlo filtering

IET Smart Grid, 2020
Quick and accurate detection of cyber-attacks is key to the normal operation of the smart grid system. In this study, joint state estimation and sequential attack detection method for a given bus with grid frequency drift is proposed that utilises the ...
Leian Chen, Xiaodong Wang
doaj   +1 more source

Variance Reduction of Sequential Monte Carlo Approach for GNSS Phase Bias Estimation

Mathematics, 2020
Global navigation satellite systems (GNSS) are an important tool for positioning, navigation, and timing (PNT) services. The fast and high-precision GNSS data processing relies on reliable integer ambiguity fixing, whose performance depends on phase bias
Yumiao Tian, Maorong Ge, Frank Neitzel
doaj   +1 more source