add_predictions: Add predictions to a data frame

In actxps: Create Actuarial Experience Studies: Prepare Data, Summarize Results, and Create Reports

Add predictions to a data frame

Description

Attach predicted values from a model to a data frame with exposure-level records.

Usage

add_predictions(.data, model, ..., col_expected = NULL)

Arguments

.data	A data frame, preferably with the class exposed_df
model	A model object that has an S3 method for predict()
...	Additional arguments passed to predict()
col_expected	NULL or a character vector containing column names for each value returned by predict()

Details

This function attaches predictions from a model to a data frame that preferably has the class exposed_df. The model argument must be a model object that has an S3 method for the predict() function. This method must have new data for predictions as the second argument.

The col_expected argument is optional.

• If NULL, names from the result of predict() will be used. If there are no names, a default name of "expected" is assumed. In the event that predict() returns multiple values, the default name will be suffixed by "_x", where x = 1 to the number of values returned.

• If a value is passed, it must be a character vector of same length as the result of predict()

Value

A data frame or exposed_df object with one of more new columns containing predictions.

Examples

expo <- expose_py(census_dat, "2019-12-31") |>
  mutate(surrender = status == "Surrender")
mod <- glm(surrender ~ inc_guar + pol_yr, expo, family = 'binomial')
add_predictions(expo, mod, type = 'response')

actxps documentation built on June 26, 2024, 9:07 a.m.