Evaluating the impact of program activities on outcomes occasionally involves complex data structures – such as units nested within clusters, and observed longitudinally – and the corresponding ...
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 ...
This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...
A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...
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