mnlogit
R package mnlogit: Multinomial Logit Model. Time and memory efficient estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed by Newton-Raphson method using an optimized, parallel C++ library to achieve fast computation of Hessian matrices. Motivated by large scale multiclass classification problems in econometrics and machine learning.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
Sorted by year (- Yves Croissant: Estimation of Random Utility Models in R: The mlogit Package (2020) not zbMATH
- Mauricio Sarrias and Ricardo Daziano: Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package (2017) not zbMATH
- Quost, Benjamin; Denoeux, Thierry; Li, Shoumei: Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression (2017)
- Asad Hasan, Wang Zhiyu, Alireza S. Mahani: Fast Estimation of Multinomial Logit Models: R Package mnlogit (2014) arXiv