Builds a symbolized_model from a brmsfit
object. v0.8 covers the Gaussian conditional submodel (identity link)
with optional (1 | g) random intercepts. Other families and brms's
distributional-parameter formulas (sigma ~ z, etc.) return capability
errors via capability_check().
Usage
# S3 method for class 'brmsfit'
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.
Credible intervals
brms is Bayesian, so the "confidence band" carried in
fixed_effects and interpretation is a 95% credible interval –
the 2.5% and 97.5% posterior quantiles. excludes_zero is the
indicator for whether the credible interval excludes zero (i.e. the
posterior puts negligible mass on either side of zero). ci_method
is set to "credible" so renderers can label the band correctly.