add_utility_predn_to_ds: Add utility prediction to dataset

In ready4-dev/specific: Specify Models to Solve Inverse Problems

Add utility prediction to dataset

Description

add_utility_predn_to_ds() is an Add function that updates an object by adding data to that object. Specifically, this function implements an algorithm to add utility prediction to dataset. Function argument data_tb specifies the object to be updated. The function returns Data (a tibble).

Usage

add_utility_predn_to_ds(
  data_tb,
  model_mdl,
  tfmn_1L_chr,
  depnt_var_nm_1L_chr,
  force_min_max_1L_lgl = T,
  force_new_data_1L_lgl = F,
  impute_1L_lgl = T,
  is_brms_mdl_1L_lgl = T,
  new_data_is_1L_chr = "Predicted",
  predn_type_1L_chr = NULL,
  predr_vars_nms_chr = NULL,
  rmv_tfd_depnt_var_1L_lgl = F,
  sd_dbl = NA_real_,
  utl_cls_fn = NULL,
  utl_min_val_1L_dbl = -1
)

Arguments

data_tb	Data (a tibble)
model_mdl	Model (a model)
tfmn_1L_chr	Transformation (a character vector of length one)
depnt_var_nm_1L_chr	Dependent variable name (a character vector of length one)
force_min_max_1L_lgl	Force minimum maximum (a logical vector of length one), Default: T
force_new_data_1L_lgl	Force new data (a logical vector of length one), Default: F
impute_1L_lgl	Impute (a logical vector of length one), Default: T
is_brms_mdl_1L_lgl	Is bayesian regression models model (a logical vector of length one), Default: T
new_data_is_1L_chr	New data is (a character vector of length one), Default: 'Predicted'
predn_type_1L_chr	Prediction type (a character vector of length one), Default: NULL
predr_vars_nms_chr	Predictor variables names (a character vector), Default: NULL
rmv_tfd_depnt_var_1L_lgl	Remove transformed dependent variable (a logical vector of length one), Default: F
sd_dbl	Standard deviation (a double vector), Default: NA
utl_cls_fn	Utility class (a function), Default: NULL
utl_min_val_1L_dbl	Utility minimum value (a double vector of length one), Default: -1

Value

Data (a tibble)

ready4-dev/specific documentation built on Oct. 13, 2023, 7:54 a.m.