validate_arg_predictors: Check and validate argument 'predictors'

In collinear: Automated Multicollinearity Management

Check and validate argument predictors

Description

Validates the argument predictors by ensuring that all provided predictors are in df and don't intersect with responses, if any.

Usage

validate_arg_predictors(
  df = NULL,
  responses = NULL,
  predictors = NULL,
  quiet = FALSE,
  function_name = NULL
)

Arguments

df	(required; dataframe, tibble, or sf) A dataframe with responses (optional) and predictors. Must have at least 10 rows for pairwise correlation analysis, and 10 * (length(predictors) - 1) for VIF. Default: NULL.
responses	(optional; character, character vector, or NULL) Name of one or several response variables in df. Default: NULL.
predictors	(optional; character vector or NULL) Names of the predictors in df. If NULL, all columns except responses and constant/near-zero-variance columns are used. Default: NULL.
quiet	(optional; logical) If FALSE, messages are printed. Default: FALSE.
function_name	(optional, character string) Name of the function performing the argument check. Default: NULL

Value

character vector: predictor names

See Also

Other argument_validation: drop_geometry_column(), validate_arg_df(), validate_arg_df_not_null(), validate_arg_encoding_method(), validate_arg_f(), validate_arg_function_name(), validate_arg_max_cor(), validate_arg_max_vif(), validate_arg_preference_order(), validate_arg_quiet(), validate_arg_responses()

Examples

data(vi_smol, vi_predictors)

x <- validate_arg_predictors(
  df = vi_smol,
  predictors = vi_predictors
)

attributes(x)$validated

collinear documentation built on Dec. 8, 2025, 5:06 p.m.