Symbolize a gllvmTMB fit (Gaussian and binomial latent-variable models)
Source:R/symbolize-gllvmtmb.R
symbolize.gllvmTMB.RdBuilds a symbolized_model from a gllvmTMB fit.
Covers the Gaussian and binomial B-tier latent-variable families:
per-trait intercepts (0 + trait), the between-unit reduced-rank loading
term (latent(0 + trait | unit, d = K)), and the optional per-trait unique
variances (unique(0 + trait | unit)). Other families and covstructs
return capability errors via capability_check().
Usage
# S3 method for class 'gllvmTMB'
symbolize(fit, symbols = NULL, units = NULL, context = NULL, ...)Arguments
- fit
A fitted statistical model object.
- symbols
Optional named character vector mapping variable names to user-supplied LaTeX symbols, e.g.
c(body_mass = "W_i", temperature = "T_i").- units
Optional named character vector mapping variable names to units, e.g.
c(body_mass = "g", temperature = "C").- context
Optional short character description of the model, e.g.
"avian body-size location-scale model".- ...
Reserved for method-specific extra arguments.
Confidence intervals
Fixed-effect estimates and Wald-style approximate CIs are pulled
from summary(fit$sd_report, "fixed"). Loadings
(\boldsymbol{\Lambda}_B) and the between-unit covariance
(\boldsymbol{\Sigma}_B) are point estimates;
parametric-bootstrap uncertainty via
gllvmTMB::bootstrap_Sigma() is on the deferred list.
References
Nakagawa, S. (forthcoming). gllvmTMB: Generalized linear latent-variable
models in TMB. https://itchyshin.github.io/gllvmTMB/