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BSW (version 0.1.2)

Fitting a Log-Binomial Model Using the Bekhit–Schöpe–Wagenpfeil (BSW) Algorithm

Description

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.

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Install

install.packages('BSW')

Monthly Downloads

235

Version

0.1.2

License

GPL (>= 3)

Issues

0

Pull Requests

0

Stars

0

Forks

0

Maintainer

Adam Bekhit

Last Published

October 6th, 2025

Functions in BSW (0.1.2)

variable_selection_bsw

Variable Selection (Forward or Backward) for models of BSW()
bsw

Fitting a log-binomial model using the Bekhit-Schöpe-Wagenpfeil (BSW) algorithm
bootbsw

Estimating bootstrap statistics of bsw()
gradF

Deriving the first derivatives of the log likelihood function of the log-binomial model in bsw()
constr

Setting the linear inequality constraints for bsw()
hess

Deriving the second partial derivatives of the log likelihood function of the log-binomial model in bsw() (Hessian matrix)
confint,bsw-method

Estimating confidence intervals of the estimated model parameters of bsw()
summary,bsw-method

Summarizing the estimated model parameters of bsw()
coef,bsw-method

Extracting the estimated model parameters of bsw()
bsw-class

S4 Class "bsw"