pigauto - Fill in Missing Species Traits Using a Phylogenetic Tree

Imputes missing species trait data for comparative analyses by combining three sources of information: phylogenetic similarity (closely related species share similar traits), cross-trait correlations (observed traits inform missing ones), and optional environmental covariates (climate, habitat, geography). Handles continuous measurements, counts, binary variables, ordered categories, unordered categories, bounded proportions, zero-inflated counts, and compositional multi-proportion data in a single call. The default method is a phylogenetic baseline calibrated on held-out data; an optional graph neural network correction, which is needed to use covariates, is blended in through a per-trait gate that retains a baseline fallback. Provides conformal prediction intervals for continuous, count, ordinal, and proportion traits and an experimental analysis-aware multiple-imputation workflow for one missing continuous covariate in Gaussian linear, binomial-logit, and Gaussian random-intercept models, with Rubin pooling limited to fixed effects. Stochastic graph-network and posterior-tree completions are prediction diagnostics rather than validated inferential imputations. Bundled datasets include 300-species and 9,993-species bird-trait subsets with matching example phylogenetic trees. Rubin (1987, ISBN:978-0-471-08705-2); Vovk et al. (2005, ISBN:978-0-387-25061-8); Nakagawa and de Villemereuil (2019) <doi:10.1093/sysbio/syy089>.