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 |
Bread for Sandwich Estimator |
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 |
confint |
confint method for maxLik objects |
confint.maxLik |
confint method for maxLik objects |
estfun |
Extract Gradients Evaluated at each Observation |
estfun.maxLik |
Extract Gradients Evaluated at each Observation |
fnSubset |
Call fnFull with variable and fixed parameters |
glance.maxLik |
tidy and glance methods for maxLik objects |
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 |
tidy.maxLik |
tidy and glance methods for maxLik objects |
vcov.maxLik |
Variance Covariance Matrix of maxLik objects |