nestedmodels (version 1.1.0)

predict.nested_model_fit: Nested Model Predictions

Description

Apply a fitted nested model to generate different types of predictions. stats::predict() / parsnip::predict_raw() methods for nested model fits.

Usage

# S3 method for nested_model_fit
predict(object, new_data, type = NULL, opts = list(), ...)
# S3 method for nested_model_fit
predict_raw(object, new_data, opts = list(), ...)

Value

A data frame of model predictions. For predict_raw(), a matrix, data frame, vector or list.

Arguments

object

A nested_model_fit object produced by fit.nested_model().

new_data

A data frame to make predictions on. Can be nested or non-nested.

type

A singular character vector or NULL. Passed on to parsnip::predict.model_fit().

opts

A list of optional arguments. Passed on to parsnip::predict.model_fit().

...

Arguments for the underlying model's predict function. Passed on to parsnip::predict.model_fit().

See Also

parsnip::predict.model_fit()

Examples

library(dplyr)
library(tidyr)
library(parsnip)

data <- filter(example_nested_data, id %in% 5:15)

nested_data <- nest(data, data = -id)

model <- linear_reg() %>%
  set_engine("lm") %>%
  nested()

fitted <- fit(model, z ~ x + y + a + b, nested_data)

predict(fitted, example_nested_data)

predict_raw(fitted, example_nested_data)