Bayesian Group Fused Priors for Deciphering Environmental Regulation of Abscission

ABSTRACT Abscission, the shedding of organismal parts, depends on physiological events whose optimal timing is crucial for species survival. Environmental variations impact species development, particularly abscission processes across multiple developmental stages, identifying which environmental factors modulate abscission and when is essential in the context of climate change. Treating environmental variables as time series‐groups of temporally correlated variables raises statistical challenges for selecting relevant groups (environmental variables) and their correlated components (time periods). We address these objectives by introducing the Bayesian fused and fusion priors through a general parameterization. We highlight a trade‐off between priors used on differences versus coefficients, demonstrating that horseshoe‐type priors on both differences and coefficients, with appropriate parameterizations, achieve effective selection, estimation and algorithmic stability regardless of group number or size. Our study focuses on fruit abscission in oil palms, which affects bunch harvest timing. Abscission disruption can impact oil yield and quality, consequently affecting economic returns. This application, based on experimental data from Benin, illustrates how our proposed priors successfully select both environmental variables and developmental stages involved in bunch harvest timing.