gradF

A numeric vector containing the initial values of the model parameters.

theta

A numeric vector containing the dependent variable of the model.

<code>gradF()</code> derives the first derivatives of the log likelihood function of the log-binomial model.

Implements a modified Newton-type algorithm (BSW algorithm) for solving the maximum likelihood estimation problem in fitting a log-binomial model under linear inequality constraints.

gradF: Deriving the first derivatives of the log likelihood function of the log-binomial model in `bsw()`

Description

Usage

Arguments

Value