maxLik
Tools for maximum likelihood (ML) estimation in R
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What is maxLik?

maxLik is an extension package for the "language and environment for statistical computing and graphics" called R.

maxLik provides tools for maximum likelihood (ML) estimations.
What can maxLik do?
 (Likelihood) maximization using the following algorithms:

NewtonRaphson (NR). This method is based on quadratic
approximation and uses both gradient and Hessian of the
function.

BerndtHallHallHausman (BHHH). A version of NR where
the Hessian is approximated by information equality (only
works for maxmizing loglikelihood).

BroydenFletcherGoldfarbShanno (BFGS). Another
quasiNewton method with a different approximation of Hessian.

conjugate gradients (CG). A method which only uses
gradients (and function values) and does not approximate
the Hessian. May be useful (but slow) for large problems.

simulated annealing (SANN). This method only uses
function values. It is a stochastic optimization method
which may be used if the objective function has secondary
maximums, and in case of nondifferentiable functions.

NelderMead (NM). A simplexbased method using only the
function values.
 Constrained maximization:
 Linear equality and inequality constraints
Who has written maxLik?
Where can I get maxLik?
 The released version is available on
CRAN
 The current development version is available on
RForge
Under which license is maxLik released?
Where can I ask questions, report bugs, or suggest new features?
Last Update: 19 October 2013