fastzeroinfl2: Fast implementation for zero-inflated Count Data Regression

In linogaliana/gravity: Gravity model with large scale data

Description

Fast implementation for zero-inflated Count Data Regression

Usage

fastzeroinfl2(
  formula,
  data,
  subset,
  na.action,
  weights,
  offset,
  dist = c("poisson", "negbin", "geometric"),
  link = c("logit", "probit", "cloglog", "cauchit", "log"),
  control = pscl::zeroinfl.control(...),
  model = TRUE,
  y = TRUE,
  x = FALSE,
  ...
)

Arguments

formula	symbolic description of the model, see details.
data	arguments controlling formula processing via model.frame.
subset	arguments controlling formula processing via model.frame.
na.action	arguments controlling formula processing via model.frame.
weights	optional numeric vector of weights.
offset	optional numeric vector with an a priori known component to be included in the linear predictor of the count model. See below for more information on offsets.
dist	character specification of count model family (a log link is always used).
link	character specification of link function in the binary zero-inflation model (a binomial family is always used).
control	a list of control arguments specified via zeroinfl.control.
model	logicals. If TRUE the corresponding components of the fit (model frame, response, model matrix) are returned.
y	logicals. If TRUE the corresponding components of the fit (model frame, response, model matrix) are returned.
x	logicals. If TRUE the corresponding components of the fit (model frame, response, model matrix) are returned.
...	arguments passed to zeroinfl.control in the default setup.

linogaliana/gravity documentation built on April 24, 2020, 2:06 a.m.