MLEbinomBCD: Maximum Likelihood Estimation for a Bivariate Binomial...

In BCD: Bivariate Distributions via Conditional Specification

Maximum Likelihood Estimation for a Bivariate Binomial Distribution via Conditional Specification

Description

Estimates the parameters of a Bivariate Binomial Conditionals via Conditional Specification using maximum likelihood.

Usage

MLEbinomBCD(data, fixed_n1 = NULL, fixed_n2 = NULL, verbose = TRUE)

Arguments

data	A data frame or matrix with columns 'X' and 'Y'
fixed_n1	known value of 'n1' (NULL to estimate)
fixed_n2	known value of 'n2' (NULL to estimate)
verbose	logical; print progress

Value

A list of class "MLEpoisBCD" containing:

n1

estimated n1

n2

estimated n2

p1

estimated p1

p2

estimated p2

lambda

estimated lambda

logLik

Maximum log-likelihood achieved.

AIC

Akaike Information Criterion.

BIC

Bayesian Information Criterion.

convergence

Convergence status from the optimizer (0 means successful).

Examples

data <- rbinomBCD(n = 10,n1 = 5, n2 = 3, p1 = 0.6, p2 = 0.4, lambda = 1.2)
MLEbinomBCD(data)
MLEbinomBCD(data, fixed_n1 = 5, fixed_n2 = 3)

BCD documentation built on June 25, 2025, 5:09 p.m.