Generalized joint attribute modeling for biodiversity analysis : Median-zero , multivariate , multifarious data

  title={Generalized joint attribute modeling for biodiversity analysis : Median-zero , multivariate , multifarious data},
  author={James S. Clark and Diana R. Nemergut and Bijan Seyednasrollah and Julia Phillip and Turner and Stacy Y. Zhang},
Probabilistic forecasts of species distribution and abundance require models that accommodate the range of ecological data, including a joint distribution of multiple species based on combinations of continuous and discrete observations, mostly zeros. We develop a generalized joint attribute model (GJAM), a probabilistic framework that readily applies to data that are combinations of presence-absence, ordinal, continuous, discrete, composition, zero-inflated, and censored. It does so as a joint… CONTINUE READING


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