Sampling from Mixture Distributions Based on Regime-Switching Diffusions

It is proposed to use stochastic differential equations with state-dependent switching 4 rates (SDEwS) for sampling from finite mixture distributions. An Euler scheme with constant time 5 step for SDEwS is considered. It is shown that the scheme converges with order one in weak sense 6 and also in the ergodic limit. Numerical experiments illustrate the use of SDEwS for sampling from 7 mixture distributions and confirm the theoretical results. 8 Key words. Stochastic differential equations with switching, hybrid switching diffusions, finite 9 mixture distributions, ergodic limits, sampling, weak numerical schemes.

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Publication Details

Journal
SIAM Journal on Scientific Computing
Published
2025-05-06
DOI
https://doi.org/10.1137/24m1677113
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Sampling from Mixture Distributions Based on Regime-Switching Diffusions

M. V. Tretyakov
SIAM Journal on Scientific Computing
Markov Chains and Monte Carlo Methods
article

Sampling from Mixture Distributions Based on Regime-Switching Diffusions

M. V. Tretyakov
article en

Abstract

It is proposed to use stochastic differential equations with state-dependent switching 4 rates (SDEwS) for sampling from finite mixture distributions. An Euler scheme with constant time 5 step for SDEwS is considered. It is shown that the scheme converges with order one in weak sense 6 and also in the ergodic limit. Numerical experiments illustrate the use of SDEwS for sampling from 7 mixture distributions and confirm the theoretical results. 8 Key words. Stochastic differential equations with switching, hybrid switching diffusions, finite 9 mixture distributions, ergodic limits, sampling, weak numerical schemes.

SIAM Journal on Scientific ComputingVol. 47(3)
University of Nottingham (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 90%
Markov Chains and Monte Carlo Methods
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