GJAM is an R package that analyzes joint attribute data (e.g., species abundance) that are combinations of continuous and discrete data with Gibbs sampling. The tutorial in the folder …

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 …

gjam exploits censoring to combine multiple data types in a single model, including mixtures of continuous and discrete data. For example, the microbial community (composition data) might …

2022年5月23日 · gjam generates an object of class "gjam", allowing it to appropriate the summary and print functions in R. To avoid conflicts with other packages, gjam function names begin …

2022年5月23日 · The generalized joint attribute model (gjam) analyzes multivariate data that are combinations of presence-absence, ordinal, continuous, discrete, composition, zero-inflated, …

The generalized joint attribute model (gjam) analyzes multivariate data that are combinations of presence-absence, ordinal, continuous, discrete, composition, zero-inflated, and censored. It …

2022年5月24日 · Analyzes joint attribute data (e.g., species abundance) with Gibbs sampling. Input can be output from gjamSimData. Returns a list of objects from Gibbs sampling that can …

2022年5月24日 · 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 …

Generalized joint attribute modeling for biodiversity analysis: Median-zero, multivariate, multifarious data, Ecological Monographs, in press. interpretation is needed on the observation …

2022年1月2日 · The first part of this tutorial covers the theoretical background of a generalized joint attribute model (GJAM), which is a multivariate hierarchical Bayesian model. GJAM has …