fepoisson: Poisson model fitting high-dimensional with k-way fixed...

In capybara: Fast and Memory Efficient Fitting of Linear Models with High-Dimensional Fixed Effects

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,
  vcov = 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.
vcov	an optional character string specifying the type of variance-covariance estimator. One of "iid" (default OLS, ignore cluster part of formula), "hetero" (heteroskedastic-robust HC0, computed in C++ - no cluster variable needed), "cluster" (one-way sandwich using the cluster variable in the formula), "m-estimator" (M-estimator one-way sandwich), or "dyadic" (Cameron-Miller dyadic sandwich; requires two entity variables in the third part of the formula). When NULL (default), the type is inferred from the formula: if a cluster variable is present the standard sandwich is used, otherwise the inverse Hessian (IID) is returned.
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 ~ 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

ross2004_subset <- ross2004[ross2004$year == 1999, ]
ross2004_subset <- ross2004_subset[ross2004_subset$ltrade >
  quantile(ross2004_subset$ltrade, 0.75), ]

fit <- fepoisson(ltrade ~ ldist, ross2004_subset)

summary(fit)

capybara documentation built on June 15, 2026, 9:10 a.m.