Generalized Joint Attribute Modeling
Generalized Joint Attribute Modeling
Gibbs sampler for gjam data
Censor gjam response data
Parameters for gjam conditional prediction
Compress (de-zero) gjam data
Fill out data for time series (state-space) gjam
Indirect effects and interactions for gjam data
Plots indirect effects and interactions for gjam data
Ordinate gjam data
Plot gjam analysis
Incidence point pattern to grid counts
Predict gjam data
Prior coefficients for gjam analysis
Expand (re-zero) gjam data
Sensitivity coefficients for gjam
Simulated data for gjam analysis
Ecological traits for gjam analysis
Trim gjam response data
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>.