3 citations · 3 across the 4 of their papers we have counts for
4 papers
Website visits can predict angler presence using machine learning
Julia S. Schmid, Sean Simmons, Mark A. Lewis +2
Understanding and predicting recreational angler effort is important for sustainable fisheries management. However, conventional methods of measuring angler effort, such as surveys…
Analyzing recreational fishing effort -- Gender differences and the impact of Covid-19
Julia S. Schmid, Sean Simmons, Mark S. Poesch +2
Recreational fishing is an important economic driver and provides multiple social benefits. To predict fishing activity, identifying variables related to variation, such as gender…
Webpage Views as a Proxy for Angler Pressure and Effort: Insights from Bayesian Networks
Azar Taheri Tayebi, Julia S. Schmid, Sean Simmons +3
Reliable angler activity data inform fisheries management. Traditionally, such data are gathered through surveys, but an innovative cost-effective approach involves utilizing onlin…
Bayesian calibration of simulation models: A tutorial and an Australian smoking behaviour model
Stephen Wade, Marianne F Weber, Peter Sarich +11
Simulation models of epidemiological, biological, ecological, and environmental processes are increasingly being calibrated using Bayesian statistics. The Bayesian approach provide…