multinomial.R
In brglm2: Bias Reduction in Generalized Linear Models

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.height = 6
)

## ----echo = TRUE--------------------------------------------------------------
library("brglm2")
data("alligators", package = "brglm2")

## ----echo = TRUE--------------------------------------------------------------
agresti_contrasts <- list(lake = contr.treatment(levels(alligators$lake), base = 4),
                          size = contr.treatment(levels(alligators$size), base = 2))
all_ml <- brmultinom(foodchoice ~ size + lake , weights = freq,
                     data = alligators,
                     contrasts = agresti_contrasts,
                     ref = 1,
                     type = "ML")
all_ml_summary <- summary(all_ml)
## Estimated regression parameters
round(all_ml_summary$coefficients, 2)
## Estimated standard errors
round(all_ml_summary$standard.errors, 2)

## ----echo = TRUE--------------------------------------------------------------
all_mean <- update(all_ml, type = "AS_mean")
summary(all_mean)

## ----echo = TRUE--------------------------------------------------------------
all_median <- update(all_ml, type = "AS_median")
summary(all_median)

## ----echo = TRUE, error = TRUE------------------------------------------------
all_ml_sparse <- update(all_ml, weights = round(freq/3), slowit = 0.1)
summary(all_ml_sparse)

## ----echo = TRUE--------------------------------------------------------------
library("detectseparation")
se_ratios <- check_infinite_estimates(all_ml_sparse)
plot(se_ratios)

## ----echo = TRUE--------------------------------------------------------------
all_mean_sparse <- update(all_ml_sparse, type = "AS_mean")
summary(all_mean_sparse)

all_median_sparse <- update(all_ml_sparse, type = "AS_median")
summary(all_median_sparse)