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Hauptverfasser: Aldous, David J., Cruz, Madelyn, Feng, Shi
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2403.18153
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author Aldous, David J.
Cruz, Madelyn
Feng, Shi
author_facet Aldous, David J.
Cruz, Madelyn
Feng, Shi
contents Consider a compact metric space $S$ and a pair $(j,k)$ with $k \ge 2$ and $1 \le j \le k$. For any probability distribution $θ\in P(S)$, define a Markov chain on $S$ by: from state $s$, take $k$ i.i.d. ($θ$) samples, and jump to the $j$'th closest. Such a chain converges in distribution to a unique stationary distribution, say $π_{j,k}(θ)$. This defines a mapping $π_{j,k}: P(S) \to P(S)$. What happens when we iterate this mapping? In particular, what are the fixed points of this mapping? A few results are proved in a companion article; this article, not intended for formal publication, records numerical studies and conjectures.
format Preprint
id arxiv_https___arxiv_org_abs_2403_18153
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Markov chains and mappings of distributions on compact spaces II: Numerics and Conjectures
Aldous, David J.
Cruz, Madelyn
Feng, Shi
Probability
60J05
Consider a compact metric space $S$ and a pair $(j,k)$ with $k \ge 2$ and $1 \le j \le k$. For any probability distribution $θ\in P(S)$, define a Markov chain on $S$ by: from state $s$, take $k$ i.i.d. ($θ$) samples, and jump to the $j$'th closest. Such a chain converges in distribution to a unique stationary distribution, say $π_{j,k}(θ)$. This defines a mapping $π_{j,k}: P(S) \to P(S)$. What happens when we iterate this mapping? In particular, what are the fixed points of this mapping? A few results are proved in a companion article; this article, not intended for formal publication, records numerical studies and conjectures.
title Markov chains and mappings of distributions on compact spaces II: Numerics and Conjectures
topic Probability
60J05
url https://arxiv.org/abs/2403.18153