R: Fit a nested model to a dataset

fit.nested_model {nestedmodels}

R Documentation

Fit a nested model to a dataset

Description

fit.model_spec() takes a nested model specification and fits the inner model specification to each nested data frame in the given dataset.

Usage

## S3 method for class 'nested_model'
fit(
  object,
  formula,
  data,
  case_weights = NULL,
  control = parsnip::control_parsnip(),
  ...
)

Arguments

`object`	An `nested_model` object (see `nested()`).
`formula`	An object of class `formula`. Passed into `parsnip::fit.model_spec()`. This should not contain the variable to nest by.
`data`	A data frame. If used with a 'nested_model' object, the data frame must already be nested.
`case_weights`	An optional vector of case weights. Passed into `parsnip::fit.model_spec()`.
`control`	A `parsnip::control_parsnip()` object. Passed into `parsnip::fit.model_spec()`.
`...`	Passed into `parsnip::fit.model_spec()`. Currently unused.

Value

A nested_model_fit object with several elements:

spec: The model specification object (the inner model of the nested model object)
fit: A tibble containing the model fits and the nests that they correspond to.
inner_names: A character vector of names, used to help with nesting the data during predictions.

Examples


library(parsnip)
library(tidyr)

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

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

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