Ancestral Inference from Functional Data: Statistical Methods and Numerical Examples
Machine Learning
2012-08-06 v1 Populations and Evolution
Quantitative Methods
Abstract
Many biological characteristics of evolutionary interest are not scalar variables but continuous functions. Here we use phylogenetic Gaussian process regression to model the evolution of simulated function-valued traits. Given function-valued data only from the tips of an evolutionary tree and utilising independent principal component analysis (IPCA) as a method for dimension reduction, we construct distributional estimates of ancestral function-valued traits, and estimate parameters describing their evolutionary dynamics.
Keywords
Cite
@article{arxiv.1208.0628,
title = {Ancestral Inference from Functional Data: Statistical Methods and Numerical Examples},
author = {Pantelis Z. Hadjipantelis and Nick S. Jones and John Moriarty and David Springate and Christopher G. Knight},
journal= {arXiv preprint arXiv:1208.0628},
year = {2012}
}