Internal function to validate the integrity of the argument df. It ensures that the dataframe has suitable dimensions for a multicollinearity analysis, transforms logical columns to numeric, character columns to factors, and converts NaN, Inf and -Inf to NA. Additionally, it checks the values of responses and predictors if these arguments are provided.
Usage
validate_arg_df(
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 exceptresponsesand 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
See also
Other argument_validation:
drop_geometry_column(),
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_predictors(),
validate_arg_preference_order(),
validate_arg_quiet(),
validate_arg_responses()
Examples
data(vi_smol, vi_predictors)
df <- validate_arg_df(
df = vi_smol,
responses = "vi_numeric",
predictors = vi_predictors_numeric,
quiet = FALSE
)
attributes(vi)$validated
#> NULL
