Symbolize a glmmTMB fit (Gaussian, v0.7 first slice) — symbolize.glmmTMB • symbolizer

Builds a symbolized_model from a glmmTMB fit. v0.7 covers the Gaussian conditional submodel (identity link) with optional (1 | g) random intercepts and an optional distributional dispformula. Other families and zero-inflation submodels return capability errors via capability_check().

Usage

# S3 method for class 'glmmTMB'
symbolize(
  fit,
  symbols = NULL,
  units = NULL,
  context = NULL,
  ci_method = "wald",
  ...
)

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".
ci_method: Confidence-interval method passed to glmmTMB::confint.glmmTMB. One of "wald" (default, fast), "profile", or "uniroot".
...: Reserved for method-specific extra arguments.

Value

A symbolized_model object.

Confidence intervals

The returned fixed_effects and interpretation tibbles carry a confidence band per coefficient: confint_low, confint_high, excludes_zero, plus a ci_method column. The default ci_method = "wald" is fast and matches confint(fit, method = "wald"). "profile" and "uniroot" are available for slower, more honest bands.

References

Brooks, M. E., Kristensen, K., van Benthem, K. J., Magnusson, A., Berg, C. W., Nielsen, A., Skaug, H. J., Maechler, M., & Bolker, B. M. (2017). glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Models. The R Journal, 9(2), 378-400.