Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation

Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation

Capturing ecological data variability in food web models is an important step for improving model representation of empirical systems. One approach is to use linear inverse modelling and Markov Chain Monte Carlo (LIM-MCMC) techniques to set up an inverse LIM problem using empirical data constraints,...

Full description

Saved in:
Bibliographic Details
Main Authors: Gemma Gerber, Ursula M. Scharler
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Ecological Informatics
Subjects:
Data variability
Food web
Markov Chain Monte Carlo
Model quality
Linear inverse modelling
Ecological network analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S1574954124004072
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S1574954124004072

Similar Items