• glmmAK

  • Referenced in 26 articles [sw13218]
  • maximum-likelihood estimation in the logistic regression with both binary (logit model) and multinomial response...
  • mnlogit

  • Referenced in 7 articles [sw21116]
  • memory efficient estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed...
  • gmnl

  • Referenced in 5 articles [sw23110]
  • implementation of maximum simulated likelihood method for the estimation of multinomial logit models with random...
  • brglm2

  • Referenced in 10 articles [sw19510]
  • maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh ... generalized linear models for binomial and multinomial responses, the adjusted score equations approach returns estimates ... always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete...
  • msgl

  • Referenced in 17 articles [sw26552]
  • package msgl: Multinomial Sparse Group Lasso. Multinomial logistic regression with sparse group lasso penalty. Simultaneous ... algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing...
  • Fmlogit

  • Referenced in 1 article [sw31895]
  • module fitting a fractional multinomial logit model by quasi maximum ... likelihood. fmlogit fits by quasi maximum likelihood a fractional multinomial logit model. It models...
  • maxent

  • Referenced in 3 articles [sw21118]
  • tools for low-memory multinomial logistic regression, also known as maximum entropy. The focus...
  • mph.fit

  • Referenced in 2 articles [sw30477]
  • mph.fit: an R program for maximum likelihood fitting of multinomial-Poisson homogeneous (MPH) models...
  • mlogitBMA

  • Referenced in 3 articles [sw11269]
  • package that can be applied to multinomial logit (MNL) data. The data is converted ... approximation. The package also contains functions for maximum likelihood estimation...
  • nlr

  • Referenced in 9 articles [sw05244]
  • models, e.g., nonlinear least squares, maximum likelihood, maximum quasi-likelihood, generalized nonlinear least squares ... choice models, such as linear-in-parameter multinomial probit models. The basic method, a generalization...
  • cta

  • Referenced in 1 article [sw41296]
  • performed based on maximum likelihood (ML) fitting of multinomial-Poisson homogeneous (MPH) and homogeneous linear...
  • penalized

  • Referenced in 1 article [sw23855]
  • extensible, and efficient MATLAB toolbox for penalized maximum likelihood. penalized allows ... generalized linear model (gaussian, logistic, poisson, or multinomial) using any of ten provided penalties ... toolbox can be extended by creating new maximum likelihood models or new penalties. The toolbox...
  • mtreatnb

  • Referenced in 1 article [sw37511]
  • Maximum simulated likelihood estimation of a negative binomial regression model with multinomial endogenous treatment...
  • gidm

  • Referenced in 1 article [sw39553]
  • maximum likelihood estimation. Specifically, the gidm command fits Poisson, negative binomial, multinomial, and ordered outcomes...
  • MGLM

  • Referenced in 3 articles [sw19421]
  • model, generalized Dirichlet multinomial model, and negative multinomial model. Making the best of the minorization ... stable and efficient algorithms to find the maximum likelihood estimates. On a multi-core machine...
  • COMODE

  • Referenced in 3 articles [sw36145]
  • simple multinomial mixture model to a constrained multinomial mixture model by incorporating constraints ... this extended model are estimated by maximum likelihood using a nonlinear constraint optimization method. Likelihood...
  • CIMTx

  • Referenced in 1 article [sw40350]
  • vector matching, Bayesian additive regression trees, targeted maximum likelihood and inverse probability of treatment weighting ... different generalized propensity score models such as multinomial logistic regression, generalized boosted models and super...
  • pmlr

  • Referenced in 1 article [sw21117]
  • MLEs in exponential family models to the multinomial logistic regression model with general covariate types ... Jeffreys prior, and yields penalized maximum likelihood estimates (PLEs) that always exist. Hypothesis testing...
  • glmdr

  • Referenced in 1 article [sw39811]
  • means it correctly handles cases where the maximum likelihood estimate (MLE) does not exist ... linear models for contingency tables and multinomial logistic regression, which it handles as conditional distributions...
  • ph2mult

  • Referenced in 0 articles [sw16511]
  • package ph2mult. Provide multinomial design methods under intersection-union test (IUT) and union-intersection test ... design types include : Minimax (minimize the maximum sample size), Optimal (minimize the expected sample size...