Learn R Programming
⚠️There's a newer version (1.5-2.1) of this package.Take me there.

maxLik (version 1.3-2)

Maximum Likelihood Estimation and Related Tools

Description

Functions for Maximum Likelihood (ML) estimation and non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the ML viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Copy Link

Version

Install

install.packages('maxLik')

Monthly Downloads

35,858

Version

1.3-2

License

GPL (>= 2)

Maintainer

Ott Toomet

Last Published

October 29th, 2015

Functions in maxLik (1.3-2)

summary.maxim

Summary method for maximization
AIC.maxLik

Methods for the various standard functions
maxLik-internal

Internal maxLik Functions
vcov.maxLik

Variance Covariance Matrix of maxLik objects
returnCode

Success or failure of the optimization
hessian

Hessian matrix
condiNumber

Print matrix condition numbers column-by-column
maxLik-package

Maximum Likelihood Estimation
MaxControl-class

Class "MaxControl"
summary.maxLik

summary the Maximum-Likelihood estimation
compareDerivatives

function to compare analytic and numeric derivatives
estfun.maxLik

Extract Gradients Evaluated at each Observation
sumt

Equality-constrained optimization
nIter

Return number of iterations for iterative models
nParam.maxim

Number of model parameters
maxBFGS

BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
maxLik

Maximum likelihood estimation
logLik.maxLik

Return the log likelihood value
maximType

Type of Minimization/Maximization
bread.maxLik

Bread for Sandwich Estimator
maxNR

Newton- and Quasi-Newton Maximization
numericGradient

Functions to Calculate Numeric Derivatives
fnSubset

Call fnFull with variable and fixed parameters
activePar

free parameters under maximisation
nObs.maxLik

Number of Observations