ewp_reg: Exponentially weighted Poisson regression model

In ewp: An Empirical Model for Underdispersed Count Data

Exponentially weighted Poisson regression model

Description

Exponentially weighted Poisson regression model

Usage

ewp_reg(
  formula,
  family = "ewp3",
  data,
  verbose = TRUE,
  method = "Nelder-Mead",
  hessian = TRUE,
  autoscale = TRUE,
  maxiter = 500,
  sum_limit = round(max(Y) * 3),
  start_val = NULL
)

Arguments

formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
family	choice of "ewp2" or "ewp3"
data	a data frame containing the variables in the model.
verbose	logical, defaults to TRUE; print model fitting progress
method	string, passed to optim, defaults to 'BFGS'
hessian	logical, defaults to TRUE; calculate Hessian?
autoscale	logical, defaults to TRUE; automatically scale model parameters inside the optimisation routine based on initial estimates from a Poisson regression.
maxiter	numeric, maximum number of iterations for optim
sum_limit	numeric, defaults to 3*maximum count; upper limit for the sum used for the normalizing factor.
start_val	list, defaults to fitting a Poisson regression; specify starting values

Value

an ewp model

ewp documentation built on June 8, 2025, 1:31 p.m.