Species richness, defined as the count of distinct bird species observed, is an important ecological indicator. Modeling species richness presents challenges due to its non-linear relationship with ...
Aim: Our aim was to develop predictive statistical models for mapping the abundance of 18 waterfowl species at a pan-Canadian level. We refined the previous generation of national waterfowl models by ...
This repository contains work for my final project for Bayesian Modeling for Biomedical Research and Public Health, BS 849 (BU School of Public Health), Spring, 2025. This was a joint project with ...
A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different ...
This is a preview. Log in through your library . Abstract The genetic architecture of fluctuating asymmetry (FA) as an estimate of developmental instability (DI) has received much attention in the ...
Flood damage processes are complex and vary between events and regions. State‐of‐the‐art flood loss models are often developed on the basis of empirical damage data from specific case studies and do ...
What Is A Hierarchical Models? Hierarchical models, also known as hierarchical statistical models, multilevel models or random-effects models, are tools for analysing data with a nested or grouped ...
We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...
https://microcollaborative.atlassian.net/wiki/spaces/DSC/pages/13828181/Confronting+models+with+data In this working group we learn about methods and ideas for ...
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