find_data: Extract data from a model object

In prediction: Tidy, Type-Safe 'prediction()' Methods

Extract data from a model object

Description

Attempt to reconstruct the data used to create a model object

Usage

find_data(model, ...)

## Default S3 method:
find_data(model, env = parent.frame(), ...)

## S3 method for class 'data.frame'
find_data(model, ...)

## S3 method for class 'crch'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'glimML'
find_data(model, ...)

## S3 method for class 'glimQL'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'glm'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'hxlr'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'lm'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'mca'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'merMod'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'svyglm'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'train'
find_data(model, ...)

## S3 method for class 'vgam'
find_data(model, env = parent.frame(), ...)

## S3 method for class 'vglm'
find_data(model, env = parent.frame(), ...)

Arguments

model	The model object.
...	Additional arguments passed to methods.
env	An environment in which to look for the data argument to the modelling call.

Details

This is a convenience function and, as such, carries no guarantees. To behave well, it typically requires that a model object be specified using a formula interface and an explicit data argument. Models that can be specified using variables from the .GlobalEnv or with a non-formula interface (e.g., a matrix of data) will tend to generate errors. find_data is an S3 generic so it is possible to expand it with new methods.

Value

A data frame containing the original data used in a modelling call, modified according to the original model's 'subset' and 'na.action' arguments, if appropriate.

See Also

prediction, build_datalist, mean_or_mode, seq_range

Examples

require("datasets")
x <- lm(mpg ~ cyl * hp + wt, data = head(mtcars))
find_data(x)

prediction documentation built on June 22, 2024, 10:18 a.m.