Presentation16: Using Maximum Likelihood Estimation to Calibrate a Discrete Time Markov Model
Channel: Mathematical Science Research Launchpad
Date: 2020-07-21

In this video lesson, we return to our example that is inspired by McAuliffe's paper on vegetation succession in desert plant communities in order to explore a method, based upon maximum likelihood estimation, for estimating the unknown transition probabilities of a discrete time markov model from the transition counts we can observe in a time series of the dominant vegetation categories seen in the landscape over time.

This video lesson supports the Probability and Statistics Core Learning Resource (CLR) (https://mathsciresearchlaunchpad.wordpress.com/probability-and-statistics/) at the Mathematical Science Research Launchpad.