Least squares estimation of the transition density in bifurcating Markov models

Fuente: arXiv
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Main Author: Penda, S. Valère Bitseki
Format: Preprint
Published: 2025
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author Penda, S. Valère Bitseki
author_facet Penda, S. Valère Bitseki
contents In this article, we propose a least squares method for the estimation of the transition density in bifurcating Markov models. Unlike the kernel estimation, this method do not use the quotient which can be a source of errors. In order to study the rate of convergence for least squares estimators, we develop exponential inequalities for empirical process of bifurcating Markov chain under bracketing assumption. Unlike the classical processes, we observe that for bifurcating Markov chains, the complexity parameter depends on the ergodicity rate and as consequence, we have that the convergence rate of our estimator is a function of the ergodicity rate. We conclude with a numerical study to validate our theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2509_12906
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Least squares estimation of the transition density in bifurcating Markov models
Penda, S. Valère Bitseki
Methodology
Probability
Statistics Theory
62G05, 60E15, 62J99, 60J80
In this article, we propose a least squares method for the estimation of the transition density in bifurcating Markov models. Unlike the kernel estimation, this method do not use the quotient which can be a source of errors. In order to study the rate of convergence for least squares estimators, we develop exponential inequalities for empirical process of bifurcating Markov chain under bracketing assumption. Unlike the classical processes, we observe that for bifurcating Markov chains, the complexity parameter depends on the ergodicity rate and as consequence, we have that the convergence rate of our estimator is a function of the ergodicity rate. We conclude with a numerical study to validate our theoretical results.
title Least squares estimation of the transition density in bifurcating Markov models
topic Methodology
Probability
Statistics Theory
62G05, 60E15, 62J99, 60J80
url https://arxiv.org/abs/2509.12906