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

I am very grateful for the opportunity to continue my research. I have been working on this project for over a year now, any this funding will allow me to wrap up my project and publish a paper with my professor. This opportunity will benefit my research as well as my goals of pursuing a PhD.
  • Major: Statistics & Applied Mathematics
  • Mentor: Benjamin Blonder, Environmental Science, Policy, & Management