Saved in:
Bibliographic Details
Main Authors: Stoehr, Julien, Robert, Christian P.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2401.16828
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909649419108352
author Stoehr, Julien
Robert, Christian P.
author_facet Stoehr, Julien
Robert, Christian P.
contents Simulating mixtures of distributions with signed weights proves a challenge as standard simulation algorithms are inefficient in handling the negative weights. In particular, the natural representation of mixture variates as associated with latent component indicators is no longer available. We propose here an exact accept-reject algorithm in the general case of finite signed mixtures that relies on optimaly pairing positive and negative components and designing a stratified sampling scheme on pairs. We analyze the performances of our approach, relative to the inverse cdf approach, since the cdf of the distribution remains available for standard signed mixtures.
format Preprint
id arxiv_https___arxiv_org_abs_2401_16828
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Simulating signed mixtures
Stoehr, Julien
Robert, Christian P.
Computation
Methodology
Simulating mixtures of distributions with signed weights proves a challenge as standard simulation algorithms are inefficient in handling the negative weights. In particular, the natural representation of mixture variates as associated with latent component indicators is no longer available. We propose here an exact accept-reject algorithm in the general case of finite signed mixtures that relies on optimaly pairing positive and negative components and designing a stratified sampling scheme on pairs. We analyze the performances of our approach, relative to the inverse cdf approach, since the cdf of the distribution remains available for standard signed mixtures.
title Simulating signed mixtures
topic Computation
Methodology
url https://arxiv.org/abs/2401.16828