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| maxLik-package | Maximum Likelihood Estimation |
| 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.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 |
| 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 |
| 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 |
| 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 | 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 |
| 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 |