SciELO - Scientific Electronic Library Online

 
vol.43 número2Method to Obtain a Vector of Hyperparameters: Application in Bernoulli TrialsPLS Generalized Linear Regression and Kernel Multilogit Algorithm (KMA) for Microarray Data Classification Problem índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Não possue artigos similaresSimilares em SciELO
  • Em processo de indexaçãoSimilares em Google

Compartilhar


Revista Colombiana de Estadística

versão impressa ISSN 0120-1751

Resumo

OROZCO-ACOSTA, Erick; LLINAS-SOLANO, Humberto  e  FONSECA-RODRIGUEZ, Javier. Convergence Theorems in Multinomial Saturated and Logistic Models. Rev.Colomb.Estad. [online]. 2020, vol.43, n.2, pp.211-231.  Epub 05-Dez-2020. ISSN 0120-1751.  https://doi.org/10.15446/rce.v43n2.79151.

In this paper, we develop a theoretical study about the logistic and saturated multinomial models when the response variable takes one of R ≥ 2 levels. Several theorems on the existence and calculations of the maximum likelihood (ML) estimates of the parameters of both models are presented and demonstrated. Furthermore, properties are identified and, based on an asymptotic theory, convergence theorems are tested for score vectors and information matrices of both models. Finally, an application of this theory is presented and assessed using data from the R statistical program.

Palavras-chave : Multinomial logit model; Saturated model; Logistic regression; Maximum likelihood estimator; Score vector; Fisher information matrix.

        · resumo em Espanhol     · texto em Inglês     · Inglês ( pdf )