fbglm {fbglm}R Documentation

Fractional binomial regression model

Description

Fit a fractional binomial regression model via maximum likelihood.

Usage

fbglm(y, x)

Arguments

y

A response vector.

x

A data frame with covariates.

Details

Fractional binomial distribution can be considered as zero-inflated, over-dispersed binomial model, and it has three parameters (p,H,c) in addition to the number of trials n. We use a specific parametrization such that p,H,c \in (0,1), and regress these parameters with logit link on the covariates, while letting n as the maximum of the response y.

Value

A list of log-likelihood, estimated coefficients, and maximum likelihood estimation results.

References

Breece, C. and Lee, J. (2024) Fractional binomial regression model for count data with excess zeros.https://arxiv.org/html/2410.08488v1

Examples

library(agridat)
library(bbmle)
sample<-sample(270, 30)
my_y<-ridout.appleshoots$roots[sample]
my_x<-data.frame(pho=ridout.appleshoots$pho[sample])
fbglm(y=my_y, x=my_x  )


[Package fbglm version 1.5.0 Index]