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maxLik (version 1.1-4)
Maximum Likelihood Estimation
Description
Tools for Maximum Likelihood Estimation
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Install
install.packages('maxLik')
Monthly Downloads
26,663
Version
1.1-4
License
GPL (>= 2)
Maintainer
Arne Henningsen
Last Published
September 16th, 2013
Functions in maxLik (1.1-4)
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summary.maxim
Summary method for maximisation/minimisation
vcov.maxLik
Variance Covariance Matrix of maxLik objects
estfun.maxLik
Extract Gradients Evaluated at each Observation
compareDerivatives
function to compare analytic and numeric derivatives
maximType
Type of Minimization/Maximization
maxNR
Newton- and Quasi-Newton Maximization
AIC.maxLik
Methods for the various standard functions
maxBFGS
BFGS, conjugate gradient, SANN and Nelder-Mead Maximization
nObs.maxLik
Number of Observations
maxLik
Maximum likelihood estimation
fnSubset
Call fnFull with variable and fixed parameters
returnCode
Return code for optimisation and other objects
condiNumber
Print matrix condition numbers column-by-column
nIter
Return number of iterations for iterative models
summary.maxLik
summary the Maximum-Likelihood estimation
returnMessage
Information about the optimisation process
nParam.maxim
Number of model parameters
sumt
Equality-constrained optimization
activePar
free parameters under maximisation
hessian
Hessian matrix
bread.maxLik
Bread for Sandwich Estimator
logLik.maxLik
Return the log likelihood value
maxLik-internal
Internal maxLik Functions
numericGradient
Functions to Calculate Numeric Derivatives