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BSW (version 0.1.1)

Fitting a Log-Binomial Model using the Bekhit-Sch<c3><b6>pe-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

208

Version

0.1.1

License

GPL (>= 3)

Issues

0

Pull Requests

0

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0

Forks

0

Maintainer

Adam Bekhit

Last Published

March 22nd, 2021

Functions in BSW (0.1.1)

summary,bsw-method

Summarizing the estimated model parameters of bsw()
hess

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

Setting the linear inequality constraints for bsw()
gradF

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

Fitting a log-binomial model using the Bekhit-Sch<U+00F6>pe-Wagenpfeil (BSW) algorithm
bsw-class

S4 Class "bsw"
coef,bsw-method

Extracting the estimated model parameters of bsw()
confint,bsw-method

Estimating confidence intervals of the estimated model parameters of bsw()