Attempt to reconstruct the data used to create a model object
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(), ...)
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.
The model object.
Additional arguments passed to methods.
An environment in which to look for the data
argument to the modelling call.
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.
prediction
, build_datalist
, mean_or_mode
, seq_range
require("datasets")
x <- lm(mpg ~ cyl * hp + wt, data = head(mtcars))
find_data(x)
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