Package: maxLik 1.5-2.2

maxLik: 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.

Authors:Ott Toomet [aut, cre], Arne Henningsen [aut], Spencer Graves [ctb], Yves Croissant [ctb], David Hugh-Jones [ctb], Luca Scrucca [ctb]

maxLik_1.5-2.2.tar.gz
maxLik_1.5-2.2.zip(r-4.7)maxLik_1.5-2.2.zip(r-4.6)maxLik_1.5-2.2.zip(r-4.5)
maxLik_1.5-2.2.tgz(r-4.6-any)maxLik_1.5-2.2.tgz(r-4.5-any)
maxLik_1.5-2.2.tar.gz(r-4.7-any)maxLik_1.5-2.2.tar.gz(r-4.6-any)
maxLik_1.5-2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
maxLik/json (API)

# Install 'maxLik' in R:
install.packages('maxLik', repos = c('https://otoomet.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

9.54 score 120 packages 920 scripts 35k downloads 11 mentions 32 exports 6 dependencies

Last updated from:88286e2d18. Checks:8 OK, 1 NOTE. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK105
source / vignettesOK267
linux-release-x86_64NOTE118
macos-release-arm64OK129
macos-oldrel-arm64OK147
windows-develOK87
windows-releaseOK82
windows-oldrelOK80
wasm-releaseOK108

Exports:activeParcompareDerivativescondiNumberfnSubsetglancegradienthessianmaxAdammaxBFGSmaxBFGSRmaxBHHHmaxCGmaxControlmaximTypemaxLikmaxNMmaxNRmaxSANNmaxSGAmaxValuenIternumericGradientnumericHessiannumericNHessianobjectiveFnreturnCodereturnMessageshowstoredParametersstoredValuessumttidy

Dependencies:digestgenericslatticemiscToolssandwichzoo

Introduction: what is maximum likelihood
Rendered fromintro-to-maximum-likelihood.Rnwusingutils::Sweave

Last update: 2021-07-26
Started: 2021-03-22

Maximum likelihood estimation with maxLik
Introduction | Basic usage | Advanced usage
Rendered fromusing-maxlik.Rnwusingutils::Sweave

Last update: 2021-03-22
Started: 2021-03-22

SGA introduction: the basic usage of maxSGA
Rendered fromstochastic-gradient-maxLik.Rnwusingutils::Sweave

Last update: 2021-03-22
Started: 2020-07-31

Readme and manuals

Help Manual

Help pageTopics
Maximum Likelihood EstimationmaxLik-package
free parameters under maximizationactivePar activePar.default
Methods for the various standard functionsAIC.maxLik coef.maxim coef.maxLik stdEr.maxLik
Bread for Sandwich Estimatorbread bread.maxLik
function to compare analytic and numeric derivativescompareDerivatives
Print matrix condition numbers column-by-columncondiNumber condiNumber.default condiNumber.maxLik
confint method for maxLik objectsconfint confint.maxLik
Call fnFull with variable and fixed parametersfnSubset
Extract Gradients Evaluated at each Observationestfun estfun.maxLik gradient gradient.maxim
Hessian matrixhessian hessian.default
Return the log likelihood valuelogLik.maxLik logLik.summary.maxLik
BFGS, conjugate gradient, SANN and Nelder-Mead MaximizationmaxBFGS maxCG maxNM maxSANN
Class '"MaxControl"'maxControl maxControl,MaxControl-method maxControl,maxim-method maxControl,missing-method MaxControl-class show,MaxControl-method
Type of Minimization/MaximizationmaximType maximType.default maximType.maxim maximType.MLEstimate
Maximum likelihood estimationmaxLik print.maxLik
Newton- and Quasi-Newton MaximizationmaxBFGSR maxBHHH maxNR
Stochastic Gradient AscentmaxAdam maxSGA
Function value at maximummaxValue maxValue.maxim
Return number of iterations for iterative modelsnIter nIter.default
Number of ObservationsnObs.maxLik
Number of model parametersnParam.maxim
Functions to Calculate Numeric DerivativesnumericGradient numericHessian numericNHessian
Optimization Objective FunctionobjectiveFn objectiveFn.maxim
Success or failure of the optimizationreturnCode returnCode.default returnCode.maxLik returnMessage returnMessage.default returnMessage.maxim returnMessage.maxLik
Return the stored values of optimizationstoredParameters storedParameters.maxim storedValues storedValues.maxim
Summary method for maximizationprint.summary.maxim summary.maxim
summary the Maximum-Likelihood estimationcoef.summary.maxLik summary.maxLik
Equality-constrained optimizationsumt
tidy and glance methods for maxLik objectsglance.maxLik tidy.maxLik
Variance Covariance Matrix of maxLik objectsvcov.maxLik