maxLik v1.4-6
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Maximum Likelihood Estimation and Related Tools
Functions for Maximum Likelihood (ML) estimation, non-linear
optimization, and related tools. It includes a unified way to call
different optimizers, and classes and methods to handle the results from
the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing
and developing your own models.
Functions in maxLik
| Name | Description | |
| bread.maxLik | Bread for Sandwich Estimator | |
| gradient | Extract Gradients Evaluated at each Observation | |
| MaxControl-class | Class "MaxControl" | |
| fnSubset | Call fnFull with variable and fixed parameters | |
| hessian | Hessian matrix | |
| logLik.maxLik | Return the log likelihood value | |
| maxBFGS | BFGS, conjugate gradient, SANN and Nelder-Mead Maximization | |
| compareDerivatives | function to compare analytic and numeric derivatives | |
| condiNumber | Print matrix condition numbers column-by-column | |
| maxLik-internal | Internal maxLik Functions | |
| activePar | free parameters under maximization | |
| maxNR | Newton- and Quasi-Newton Maximization | |
| maxValue | Function value at maximum | |
| maxSGA | Stochastic Gradient Ascent | |
| maximType | Type of Minimization/Maximization | |
| AIC.maxLik | Methods for the various standard functions | |
| objectiveFn | Optimization Objective Function | |
| vcov.maxLik | Variance Covariance Matrix of maxLik objects | |
| returnCode | Success or failure of the optimization | |
| sumt | Equality-constrained optimization | |
| maxLik | Maximum likelihood estimation | |
| maxLik-package | Maximum Likelihood Estimation | |
| summary.maxim | Summary method for maximization | |
| nIter | Return number of iterations for iterative models | |
| nParam.maxim | Number of model parameters | |
| nObs.maxLik | Number of Observations | |
| storedValues | Return the stored values of optimization | |
| numericGradient | Functions to Calculate Numeric Derivatives | |
| summary.maxLik | summary the Maximum-Likelihood estimation | |
| No Results! | ||
Vignettes of maxLik
| Name | ||
| auto/stochastic-gradient-maxLik.el | ||
| sga.bib | ||
| stochastic-gradient-maxLik.Rnw | ||
| No Results! | ||
Last month downloads
Details
| Date | 2020-11-24 |
| License | GPL (>= 2) |
| ByteCompile | yes |
| NeedsCompilation | no |
| Packaged | 2020-11-24 15:51:02 UTC; ott |
| Repository | CRAN |
| Date/Publication | 2020-11-24 16:30:05 UTC |
| suggests | clue , dlm , MASS , testthat |
| depends | methods , miscTools (>= 0.6-8) , R (>= 2.4.0) |
| imports | sandwich |
| Contributors | Arne Henningsen, Ott Toomet |
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