# Maximum Likelihood Estimation and Related Tools

## Documentation for package ‘maxLik’ version 1.4-8

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

maxLik-package | Maximum Likelihood Estimation
activePar | free parameters under maximization
activePar.default | free parameters under maximization
AIC.maxLik | Methods for the various standard functions
bread.maxLik | Bread for Sandwich Estimator
coef.maxim | Methods for the various standard functions
coef.maxLik | Methods for the various standard functions
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
gradient | Extract Gradients Evaluated at each Observation
gradient.maxim | Extract Gradients Evaluated at each Observation
hessian | Hessian matrix
hessian.default | Hessian matrix
logLik.maxLik | Return the log likelihood value
logLik.summary.maxLik | Return the log likelihood value
maxAdam | Stochastic Gradient Ascent
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
maxControl | Class '"MaxControl"'
MaxControl-class | Class '"MaxControl"'
maxControl-method | Class '"MaxControl"'
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
maxSGA | Stochastic Gradient Ascent
maxValue | Function value at maximum
maxValue.maxim | Function value at maximum
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
objectiveFn | Optimization Objective Function
objectiveFn.maxim | Optimization Objective Function
print.maxLik | Maximum likelihood estimation
print.summary.maxim | Summary method for maximization
returnCode | Success or failure of the optimization
returnCode.default | Success or failure of the optimization
returnCode.maxLik | Success or failure of the optimization
returnMessage | Success or failure of the optimization
returnMessage.default | Success or failure of the optimization
returnMessage.maxim | Success or failure of the optimization
returnMessage.maxLik | Success or failure of the optimization
show-method | Class '"MaxControl"'
stdEr.maxLik | Methods for the various standard functions
storedParameters | Return the stored values of optimization
storedParameters.maxim | Return the stored values of optimization
storedValues | Return the stored values of optimization
storedValues.maxim | Return the stored values of optimization
summary.maxim | Summary method for maximization
summary.maxLik | summary the Maximum-Likelihood estimation
sumt | Equality-constrained optimization
vcov.maxLik | Variance Covariance Matrix of maxLik objects