Predict from a mb_analyses object

Returns IC-weighted model-averaged predictions across an mb_analyses list.

Usage

# S3 method for class 'mb_analyses'
predict(
  object,
  new_data = data_set(object),
  new_expr = NULL,
  new_values = list(),
  term = "prediction",
  conf_level = getOption("mb.conf_level", 0.95),
  modify_new_data = NULL,
  ref_data = FALSE,
  ref_fun2 = proportional_change2,
  new_expr_vec = getOption("mb.new_expr_vec", FALSE),
  parallel = getOption("mb.parallel", FALSE),
  quiet = getOption("mb.quiet", TRUE),
  ...
)

Arguments

object

An object inheriting from class mb_analysis.

new_data

A data frame at which to derive the term. Pass character(0) to extract a scalar term from new_expr.

new_expr

An R expression (e.g. { ... }) or a character string of R code specifying the predictive relationship. If NULL, uses the expression set in model() and stored in the mb_analysis object.

new_values

A named list of new or replacement values to pass to new_expr.

term

A string of the term in new_expr.

conf_level

A number specifying the confidence level. By default 0.95.

modify_new_data

A single argument function to modify new data (in list form) immediately prior to calculating new_expr.

ref_data

A flag or a data frame with 1 row indicating the reference values for calculating the effects size. If FALSE, no reference applied. If TRUE, the reference is a 1 row data.frame with all variables held at reference value.

ref_fun2

A function whose first argument takes a vector of two numbers and returns a scalar of a metric of the difference between them.

new_expr_vec

A flag specifying whether to vectorize the new_expr code.

parallel

A flag indicating whether to do predictions using parallel backend provided by foreach.

quiet

A flag indicating whether to disable tracing information.

...

Additional arguments.

Value

A data frame with one row per row of new_data.

See also

predict.mb_analysis() for full argument documentation and examples.