Return to search

Parameter Estimation in Random Differential Equation Models

We consider two distinct techniques for estimating random parameters in random differential equation (RDE) models. In one approach, the solution to a RDE is represented by a collection of solution trajectories in the form of sample deterministic equations. In a second approach we employ pointwise equivalent stochastic differential equation (SDE) representations for certain RDEs. Each of the approaches is tested using deterministic model comparison techniques for a logistic growth model which is viewed as a special case of a more general Bernoulli growth model. We demonstrate efficacy of the preferred method with experimental data using algae growth model comparisons.

Identiferoai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-11986
Date01 January 2017
CreatorsBanks, H. T., Joyner, M. L.
PublisherDigital Commons @ East Tennessee State University
Source SetsEast Tennessee State University
Detected LanguageEnglish
Typetext
SourceETSU Faculty Works

Page generated in 0.002 seconds