Small-time approximation of the transition density for diffusions with singularities. Application to the Wright-Fisher model

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Main Authors: Roa, Tania, Fariello, María Inés, Martínez, Gerardo, León, José
Format: Preprint
Published: 2022
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author Roa, Tania
Fariello, María Inés
Martínez, Gerardo
León, José
author_facet Roa, Tania
Fariello, María Inés
Martínez, Gerardo
León, José
contents The Wright-Fisher (W-F) diffusion model serves as a foundational framework for interpreting population evolution through allele frequency dynamics over time. Despite the known transition probability between consecutive generations, an exact analytical expression for the transition density at arbitrary time intervals remains elusive. Commonly utilized distributions such as Gaussian or Beta inadequately address the fixation issue at extreme allele frequencies (0 or 1), particularly for short periods. In this study, we introduce two alternative parametric functions, namely the Asymptotic Expansion (AE) and the Gaussian approximation (GaussA), derived through probabilistic methodologies, aiming to better approximate this density. The AE function provides a suitable density for allele frequency distributions, encompassing extreme values within the interval [0,1]. Additionally, we outline the range of validity for the GaussA approximation. While our primary focus is on W-F diffusion, we demonstrate how our findings extend to other diffusion models featuring singularities. Through simulations of allele frequencies under a W-F process and employing a recently developed adaptive density estimation method, we conduct a comparative analysis to assess the fit of the proposed densities against the Beta and Gaussian distributions.
format Preprint
id arxiv_https___arxiv_org_abs_2212_11442
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Small-time approximation of the transition density for diffusions with singularities. Application to the Wright-Fisher model
Roa, Tania
Fariello, María Inés
Martínez, Gerardo
León, José
Methodology
Probability
60J60, 60J70, 35C20
The Wright-Fisher (W-F) diffusion model serves as a foundational framework for interpreting population evolution through allele frequency dynamics over time. Despite the known transition probability between consecutive generations, an exact analytical expression for the transition density at arbitrary time intervals remains elusive. Commonly utilized distributions such as Gaussian or Beta inadequately address the fixation issue at extreme allele frequencies (0 or 1), particularly for short periods. In this study, we introduce two alternative parametric functions, namely the Asymptotic Expansion (AE) and the Gaussian approximation (GaussA), derived through probabilistic methodologies, aiming to better approximate this density. The AE function provides a suitable density for allele frequency distributions, encompassing extreme values within the interval [0,1]. Additionally, we outline the range of validity for the GaussA approximation. While our primary focus is on W-F diffusion, we demonstrate how our findings extend to other diffusion models featuring singularities. Through simulations of allele frequencies under a W-F process and employing a recently developed adaptive density estimation method, we conduct a comparative analysis to assess the fit of the proposed densities against the Beta and Gaussian distributions.
title Small-time approximation of the transition density for diffusions with singularities. Application to the Wright-Fisher model
topic Methodology
Probability
60J60, 60J70, 35C20
url https://arxiv.org/abs/2212.11442