Learn R Programming

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

maxLik (version 1.4-6)

Maximum Likelihood Estimation and Related Tools

Description

Functions for Maximum Likelihood (ML) estimation, 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 Maximum Likelihood 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

24,551

Version

1.4-6

License

GPL (>= 2)

Maintainer

Ott Toomet

Last Published

November 24th, 2020

Functions in maxLik (1.4-6)

Bread for Sandwich Estimator

Extract Gradients Evaluated at each Observation

MaxControl-class

Class "MaxControl"

Call fnFull with variable and fixed parameters

Return the log likelihood value

BFGS, conjugate gradient, SANN and Nelder-Mead Maximization

compareDerivatives

function to compare analytic and numeric derivatives

Print matrix condition numbers column-by-column

maxLik-internal

Internal maxLik Functions

free parameters under maximization

Newton- and Quasi-Newton Maximization

Function value at maximum

Stochastic Gradient Ascent

Type of Minimization/Maximization

Methods for the various standard functions

Optimization Objective Function

Variance Covariance Matrix of maxLik objects

Success or failure of the optimization

Equality-constrained optimization

Maximum likelihood estimation

Maximum Likelihood Estimation

Summary method for maximization

Return number of iterations for iterative models

Number of model parameters

Number of Observations

Return the stored values of optimization

numericGradient

Functions to Calculate Numeric Derivatives

summary the Maximum-Likelihood estimation