  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.
