Version 1
: Received: 14 October 2024 / Approved: 14 October 2024 / Online: 15 October 2024 (11:45:50 CEST)
How to cite:
Hoang, C.; Phan, T. A.; Tian, J. P. Stochastic Models for Ontogenetic Growth. Preprints2024, 2024101115. https://doi.org/10.20944/preprints202410.1115.v1
Hoang, C.; Phan, T. A.; Tian, J. P. Stochastic Models for Ontogenetic Growth. Preprints 2024, 2024101115. https://doi.org/10.20944/preprints202410.1115.v1
Hoang, C.; Phan, T. A.; Tian, J. P. Stochastic Models for Ontogenetic Growth. Preprints2024, 2024101115. https://doi.org/10.20944/preprints202410.1115.v1
APA Style
Hoang, C., Phan, T. A., & Tian, J. P. (2024). Stochastic Models for Ontogenetic Growth. Preprints. https://doi.org/10.20944/preprints202410.1115.v1
Chicago/Turabian Style
Hoang, C., Tuan Anh Phan and Jianjun Paul Tian. 2024 "Stochastic Models for Ontogenetic Growth" Preprints. https://doi.org/10.20944/preprints202410.1115.v1
Abstract
Based on allometric theory and scaling laws, numerous mathematical models have been proposed to study ontogenetic growth patterns of animals. Although deterministic models have provided valuable insight into growth dynamics, animal growth often deviates from strict deterministic patterns due to stochastic factors such as genetic variation and environmental fluctuations. In this study, we extend a general model for ontogenetic growth proposed by West et al. to stochastic models for ontogenetic growth by incorporating stochasticity using white noise. According to data variance fitting for stochasticity, we propose two stochastic models for ontogenetic growth, one is for determinate growth and one is for indeterminate growth. To develop a universal stochastic process for ontogenetic growth across diverse species, we approximate stochastic trajectories of two stochastic models and apply random time change and obtain a geometric Brownian motion with a multiplier of an exponential time factor. We conduct detailed mathematical analysis and numerical analysis for our stochastic models. Our stochastic models predict well not only average growth, but also variations of growth within species. This stochastic framework may be extended to studies of other growth phenomena.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
