Abstract

Score matching (Hyvarinen, 2005) is an estimation technique that avoids normalising constants in model densities (i.e. it works on improper densities) and can thus be used in many cases that maximum likelihood estimation cannot.  Unfortunately, the implementation of score matching estimators often requires tedious calculus, especially for models of data that lie on multidimensional manifolds.  I have developed an R package that uses automatic differentiation to make implementation much faster.  The package already contains estimators for compositional data models and directional distributions.

Speaker

Kassell Hinge

Research Area

Statistics seminar

Affiliation

Australian National University

Date

Friday, 28 April 2023, 4pm

Venue

Zoom (link below)