prediction (version 0.3.17)

find_data: Extract data from a model object

Description

Attempt to reconstruct the data used to create a model object

Usage

find_data(model, ...)
# S3 method for default
find_data(model, env = parent.frame(), ...)
# S3 method for data.frame
find_data(model, ...)
# S3 method for crch
find_data(model, env = parent.frame(), ...)
# S3 method for glimML
find_data(model, ...)
# S3 method for glm
find_data(model, env = parent.frame(), ...)
# S3 method for hxlr
find_data(model, env = parent.frame(), ...)
# S3 method for lm
find_data(model, env = parent.frame(), ...)
# S3 method for mca
find_data(model, env = parent.frame(), ...)
# S3 method for merMod
find_data(model, env = parent.frame(), ...)
# S3 method for svyglm
find_data(model, env = parent.frame(), ...)
# S3 method for train
find_data(model, ...)
# S3 method for vgam
find_data(model, env = parent.frame(), ...)
# S3 method for vglm
find_data(model, env = parent.frame(), ...)

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.

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.

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)