# Maximum Likelihood Estimation

## Documentation for package ‘maxLik’ version 1.2-0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

activePar | free parameters under maximisation
activePar.default | free parameters under maximisation
AIC.maxLik | Methods for the various standard functions
bread.maxLik | Bread for Sandwich Estimator
coef.maxLik | Maximum likelihood estimation
coef.summary.maxLik | summary the Maximum-Likelihood estimation
compareDerivatives | function to compare analytic and numeric derivatives
condiNumber | Print matrix condition numbers column-by-column
condiNumber.default | Print matrix condition numbers column-by-column
condiNumber.maxLik | Print matrix condition numbers column-by-column
estfun.maxLik | Extract Gradients Evaluated at each Observation
fnSubset | Call fnFull with variable and fixed parameters
hessian | Hessian matrix
hessian.default | Hessian matrix
logLik.maxLik | Return the log likelihood value
logLik.summary.maxLik | Return the log likelihood value
maxBFGS | BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
maxBFGSR | Newton- and Quasi-Newton Maximization
maxBHHH | Newton- and Quasi-Newton Maximization
maxCG | BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
maximType | Type of Minimization/Maximization
maximType.default | Type of Minimization/Maximization
maximType.maxim | Type of Minimization/Maximization
maximType.MLEstimate | Type of Minimization/Maximization
maxLik | Maximum likelihood estimation
maxNM | BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
maxNR | Newton- and Quasi-Newton Maximization
maxSANN | BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
nIter | Return number of iterations for iterative models
nIter.default | Return number of iterations for iterative models
nObs.maxLik | Number of Observations
nParam.maxim | Number of model parameters
numericGradient | Functions to Calculate Numeric Derivatives
numericHessian | Functions to Calculate Numeric Derivatives
numericNHessian | Functions to Calculate Numeric Derivatives
print.maxLik | Maximum likelihood estimation
returnCode | Return code for optimisation and other objects
returnCode.default | Return code for optimisation and other objects
returnMessage | Information about the optimisation process
returnMessage.default | Information about the optimisation process
returnMessage.maxim | Information about the optimisation process
returnMessage.maxLik | Information about the optimisation process
std.maxlik | Methods for the various standard functions
summary.maxim | Summary method for maximisation/minimisation
summary.maxLik | summary the Maximum-Likelihood estimation
sumt | Equality-constrained optimization
vcov.maxLik | Variance Covariance Matrix of maxLik objects