genmodel: Generating Model Structure

In penppml: Penalized Poisson Pseudo Maximum Likelihood Regression

Generating Model Structure

Description

genmodel transforms a data frame into the needed components for our main functions (a y vector, a x matrix and a fes list).

Usage

genmodel(
  data,
  dep = NULL,
  indep = NULL,
  fixed = NULL,
  cluster = NULL,
  selectobs = NULL
)

Arguments

data	A data frame containing all relevant variables.
dep	A string with the name of the independent variable or a column number.
indep	A vector with the names or column numbers of the regressors. If left unspecified, all remaining variables (excluding fixed effects) are included in the regressor matrix.
fixed	A vector with the names or column numbers of factor variables identifying the fixed effects, or a list with the desired interactions between variables in data.
cluster	Optional. A string with the name of the clustering variable or a column number. It's also possible to input a vector with several variables, in which case the interaction of all of them is taken as the clustering variable.
selectobs	Optional. A vector indicating which observations to use.

Value

A list with four elements:

• y: y vector.

• x: x matrix.

• fes: list of fixed effects.

• cluster: cluster vector.

penppml documentation built on Sept. 8, 2023, 5:58 p.m.