Maxlik

Maxlik: a package for maximum likelihood estimation in R. This paper describes the package maxLik for the statistical environment R. The package is essentially a unified wrapper interface to various optimization routines, offering easy access to likelihood-specific features like standard errors or information matrix equality (BHHH method). More advanced features of the optimization algorithms, such as forcing the value of a particular parameter to be fixed, are also supported.


References in zbMATH (referenced in 30 articles , 1 standard article )

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  1. Kılıç, Muhammet Burak; Şahin, Yusuf; Koca, Melih Burak: Genetic algorithm approach with an adaptive search space based on EM algorithm in two-component mixture Weibull parameter estimation (2021)
  2. Korkmaz, Mustafa Ç.; Chesneau, Christophe: On the unit Burr-XII distribution with the quantile regression modeling and applications (2021)
  3. Wei, Zheng; Conlon, Erin M.; Wang, Tonghui: Asymmetric dependence in the stochastic frontier model using skew normal copula (2021)
  4. Frery, Alejandro C.; Gambini, Juliana: Comparing samples from the (\mathcalG^0) distribution using a geodesic distance (2020)
  5. Ikechukwu, Agu Friday; Jaspa, Okoi Emmanuel; Emmanuel, Runyi Francis; Adeyinka, Ogunsanya: A three parameter shifted exponential distribution: properties and applications (2020)
  6. Diallo, Alpha Oumar; Diop, Aliou; Dupuy, Jean-François: Estimation in zero-inflated binomial regression with missing covariates (2019)
  7. Espinosa, Javier; Hennig, Christian: A constrained regression model for an ordinal response with ordinal predictors (2019)
  8. Graf, Monique; Marín, J. Miguel; Molina, Isabel: A generalized mixed model for skewed distributions applied to small area estimation (2019)
  9. Padayachee, Trishanta; Khamiakova, Tatsiana; Shkedy, Ziv; Salo, Perttu; Perola, Markus; Burzykowski, Tomasz: A multivariate linear model for investigating the association between gene-module co-expression and a continuous covariate (2019)
  10. Santana, Tiago V. F.; Ortega, Edwin M. M.; Cordeiro, Gauss M.: Generalized beta Weibull linear model: estimation, diagnostic tools and residual analysis (2019)
  11. Aragon, Davi C.; Achcar, Jorge A.; Martinez, Edson Z.: Maximum likelihood and Bayesian estimators for the double Poisson distribution (2018)
  12. Diallo, Alpha Oumar; Diop, Aliou; Dupuy, Jean-François: Analysis of multinomial counts with joint zero-inflation, with an application to health economics (2018)
  13. Louzada, Francisco; Shimizu, Taciana K. O.; Suzuki, Adriano K.; Mazucheli, Josmar; Ferreira, Paulo H.: Compositional regression modeling under tilted normal errors: an application to a Brazilian Super League Volleyball data set (2018)
  14. Pruim, Randall: Foundations and applications of statistics. An introduction using R (2018)
  15. Rodrigues, Giovani Carrara; Louzada, Francisco; Ramos, Pedro Luiz: Poisson-exponential distribution: different methods of estimation (2018)
  16. Yu, Jun; Kong, Xiangshun; Ai, Mingyao; Tsui, Kwok Leung: Optimal designs for dose-response models with linear effects of covariates (2018)
  17. Emanuele Giorgi and Peter Diggle: PrevMap: An R Package for Prevalence Mapping (2017) not zbMATH
  18. Godwin, Ryan T.: One-inflation and unobserved heterogeneity in population size estimation (2017)
  19. Lee, Kyungsub; Seo, Byoung Ki: Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data (2017)
  20. Kosmidis, Ioannis; Karlis, Dimitris: Model-based clustering using copulas with applications (2016)

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