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gjam - Generalized Joint Attribute Modeling
Analyzes joint attribute data (e.g., species abundance) that are combinations of continuous and discrete data with Gibbs sampling. Full model and computation details are described in Clark et al. (2018) <doi:10.1002/ecm.1241>.
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openblascppopenmp
3.13 score 134 scripts 479 downloadsmastif - Mast Inference and Forecasting
Analyzes production and dispersal of seeds dispersed from trees and recovered in seed traps. Motivated by long-term inventory plots where seed collections are used to infer seed production by each individual plant.
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openblascpp
2.00 score 344 downloads