rpart_exposure {offsetreg} | R Documentation |
Poisson Recursive Partitioning and Regression Trees with Exposures
Description
This function is a wrapper around rpart::rpart()
for Poisson regression
trees using weighted exposures (observation times).
Usage
rpart_exposure(
formula,
data,
exposure_col = "exposure",
weights = NULL,
control,
cost,
shrink = 1,
...
)
Arguments
formula |
A model formula that contains a single response variable on the left-hand side. |
data |
Optional. A data frame containing variables used in the model. |
exposure_col |
Character string. The name of a column in |
weights |
Optional weights to use in the fitting process. |
control |
A list of hyperparameters. See |
cost |
A vector of non-negative costs for each variable in the model. |
shrink |
Optional parameter for the splitting function. Coefficient of variation of the prior distribution. |
... |
Alternative input for arguments passed to
|
Details
Outside of the tidymodels
ecosystem, rpart_exposure()
has no
advantages over rpart::rpart()
since that function allows for exposures to
be specified in the formula interface by passing cbind(exposure, y)
as a
response variable.
Within tidymodels
, rpart_exposure()
provides an advantage because
it will ensure that exposures are included in the data whenever resamples are
created.
The formula
, data
, weights
, control
, and cost
arguments have the
same meanings as rpart::rpart()
. shrink
is passed to rpart::rpart()
's
parms
argument via a named list. See that function's documentation for full
details.
Value
An rpart
model
See Also
Examples
rpart_exposure(deaths ~ age_group + gender, us_deaths,
exposure_col = "population")