URAP

Daniel Chen

Inferential methods for n-dimensional hypervolumes

N-dimensional hypervolumes are a popular method of modeling ecological niches and functional diversity; for example, each axis in an n-dimensional niche represents an abiotic factor that is required for the survival of an organism. Many mathematical methods have been developed for constructing hypervolumes, but there are currently no methods for constructing confidence intervals or performing statistical tests. I have added inference methods to the r package “hypervolume” including a nonparametric multivariate test based on overlap statistics. I will be investigating the statistical properties of these methods compared to other nonparametric multivariate tests as well as exploring the applications of these methods in ecology.

Message to Sponsor

Being able to use this summer to write a paper on my research results is a privilege most undergrads do not get. I am deeply grateful for the opportunity as it will boost my chances of doing more research in a PhD program and beyond.
  • Major: Statistics & Applied Mathematics
  • Mentor: Benjamin Blonder, Environmental Science, Policy, & Management