Open Collections

Statistical parameter estimation and inference for dynamical models (motivate breakout A)

Banff International Research Station for Mathematical Innovation and Discovery

In the study of biological, ecological, or environmental dynamical processes, many theoretical models have been developed but it is not common practice to estimate model parameters using statistical functions of observed data. In this talk we present an overview of methods that have been proposed to enable statistical inference for parameters of dynamical models such as ordinary differential equation, continuous-time Markov chain, and stochastic differential equation models. A challenge for statisticians is to develop methods to address the issue of the computationally intensive or intractable likelihoods required for these problems.

Mathematics; Statistics; Probability theory and stochastic processes

video/mp4

Author affiliation: Colorado State University

2018-01-07

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/64306

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/