Results 91 to 100 of about 151,127 (170)

Sequential Monte Carlo testing by betting

Journal of the Royal Statistical Society Series B: Statistical Methodology
Abstract In a Monte Carlo test, the observed dataset is fixed, and several resampled or permuted versions of the dataset are generated in order to test a null hypothesis that the original dataset is exchangeable with the resampled/permuted ones.
Lasse Fischer, Aaditya Ramdas
openaire   +2 more sources

Sequential Monte Carlo Squared for online inference in stochastic epidemic models

Epidemics
Effective epidemic modeling and surveillance require computationally efficient methods that can continuously update parameter estimates as new data becomes available.
Dhorasso Temfack, Jason Wyse
doaj   +1 more source

Fixed-Lag Sequential Monte Carlo

, 2004
Publication in the conference proceedings of EUSIPCO, Viena, Austria ...
Arnaud Doucet, Stéphane Sénécal
openaire   +3 more sources

Unconventional phase separation in the model 2D spin-pseudospin system

EPJ Web of Conferences, 2018
The competition of charge and spin orderings is a challenging problem for strongly correlated systems, in particular, for high-Tc cuprates. We addressed a simplified static 2D spin-pseudospin model which takes into account both conventional spin exchange
Budrin K.S., Panov Yu.D., Moskvin A.S., Chikov A.A.   +3 more
doaj   +1 more source

Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox

Journal of Statistical Software, 2015
This paper presents the MATLAB package DeCo (density combination) which is based on the paper by Billio, Casarin, Ravazzolo, and van Dijk (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from ...
Roberto Casarin, Stefano Grassi, Francesco Ravazzolo, Herman K. van Dijk   +3 more
doaj   +1 more source

Enhancing Ligand and Protein Sampling Using Sequential Monte Carlo. [PDF]

J Chem Theory Comput, 2022
Suruzhon M, Bodnarchuk MS, Ciancetta A, Wall ID, Essex JW.   +4 more
europepmc   +1 more source

Sequential monte carlo samplers

, 2002
This paper shows how one can use Sequential Monte Carlo methods to perform what is typically done using Markov chain Monte Carlo methods. This leads to a general class of principled integration and genetic type optimization methods based on interacting particle systems.
Del Moral, Pierre, Doucet, Arnaud
openaire   +2 more sources

Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo. [PDF]

Front Genet, 2021
Yu K, Cui Z, Sui X, Qiu X, Zhang J.
europepmc   +1 more source

Cutting-Edge Monte Carlo Framework: Novel “Walk on Equations” Algorithm for Linear Algebraic Systems

Axioms
In this paper, we introduce the “Walk on Equations” (WE) Monte Carlo algorithm, a novel approach for solving linear algebraic systems. This algorithm shares similarities with the recently developed WE MC method by Ivan Dimov, Sylvain Maire, and Jean ...
Venelin Todorov, Ivan Dimov
doaj   +1 more source

Sequential Monte Carlo Methods for Protein Folding

, 2004
We describe a class of growth algorithms for finding low energy states of heteropolymers. These polymers form toy models for proteins, and the hope is that similar methods will ultimately be useful for finding native states of real proteins from ...
Grassberger, Peter
core   +1 more source