Skip to contents

emmeans support for bmmfit objects

Source: R/emmeans.R
emmeans-bmmfit.Rd

These S3 methods allow emmeans::emmeans() to work seamlessly with bmmfit objects by automatically resolving whether a parameter is a distributional (dpar) or non-linear (nlpar) parameter in brms. Users can always use dpar = "parameter_name" regardless of internal classification.

Usage

# S3 method for class 'bmmfit'
recover_data(object, ..., dpar = NULL, nlpar = NULL)

# S3 method for class 'bmmfit'
emm_basis(object, trms, xlev, grid, ..., dpar = NULL, nlpar = NULL)

Arguments

object

A bmmfit object (created by bmm())

...

Additional arguments passed to the brmsfit methods.

dpar

Character string. Name of the model parameter (e.g., "kappa", "c", "thetat"). Automatically resolved to the correct brms parameter type.

nlpar

Character string. Explicit non-linear parameter name. If provided, takes precedence over dpar.

trms, xlev, grid

Arguments passed by emmeans internally.

Value

See emmeans::recover_data() and emmeans::emm_basis() for return values.

Details

bmm models use two types of parameters internally in brms:

  • Distributional parameters (dpar): Used in models with custom_family(dpars = ...) (e.g., SDM, EZDM)

  • Non-linear parameters (nlpar): Used in models with bmf2bf() + nlf() (e.g., mixture2p, mixture3p, IMM, M3)

Users should not need to know this distinction. These methods intercept the dpar argument and, if the parameter is actually an nlpar, silently re-route it to nlpar.

See also

emmeans::emmeans()

Examples

if (FALSE) { # \dontrun{
# Works for any bmm model — no need to know dpar vs nlpar
em <- emmeans(fit, ~ condition, dpar = "kappa")
pairs(em)
confint(em)
} # }