glm-methods: Methods for 'glm' Models

In jrnold/marfx: Yet Another Marginal Effects Package

Description

Methods for glm Models

Usage

## S3 method for class 'glm'
fdfx(x, data1, data2, delta = 1, n = 1000L, confint = 0.95,
  response = TRUE, ...)

## S3 method for class 'glm'
afdfx(x, data1, data2, delta = 1, n = 1000L, confint = 0.95,
  response = TRUE, weights = NULL, ...)

## S3 method for class 'glm'
simev(x, data = stats::model.frame(x), response = TRUE,
  n = 1000L, ...)

## S3 method for class 'glm'
simfdfx(x, data1, data2, n = 1L, delta = 1,
  response = FALSE, ...)

## S3 method for class 'glm'
simpar(x, n = 1L, V = NULL, ...)

Arguments

x	object
data1, data2, data	Data
delta	Size of the difference
n	Number of iterations
confint	Confidence interval level
response	If response is true, then partial effects are on the the scale of the response variable. If false, then the partial effects are on the scale of the linear predictors.
...	further arguments passed to or from other methods.
weights	Weights to apply to the data
V	The variance-covariance matrix of the coefficients. This arguments allows for the substitution of "robust" covariance matrices.

jrnold/marfx documentation built on May 20, 2019, 1:03 a.m.