| fepoisson {capybara} | R Documentation |
Poisson model fitting high-dimensional with k-way fixed effects
Description
A wrapper for feglm with
family = poisson().
Usage
fepoisson(
formula = NULL,
data = NULL,
weights = NULL,
beta_start = NULL,
eta_start = NULL,
offset = NULL,
control = NULL
)
Arguments
formula |
an object of class "formula": a symbolic description of the model to be fitted. formula
must be of type response ~ slopes | fixed_effects | cluster.
|
data |
an object of class "data.frame" containing the variables in the model. The expected input is a
dataset with the variables specified in formula and a number of rows at least equal to the number of variables
in the model.
|
weights |
an optional string with the name of the prior weights variable in data.
|
beta_start |
an optional vector of starting values for the structural parameters in the linear predictor.
Default is \boldsymbol{\beta} = \mathbf{0}.
|
eta_start |
an optional vector of starting values for the linear predictor. |
offset |
an optional formula or numeric vector specifying an a priori known component to be included in the
linear predictor. If a formula, it should be of the form ~ log(variable).
|
control |
a named list of parameters for controlling the fitting process. See fit_control for details. |
Value
A named list of class "feglm".
Examples
# check the feglm examples for the details about clustered standard errors
mod <- fepoisson(mpg ~ wt | cyl, mtcars)
summary(mod)