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AdequacyModel: An R package for probability distributions and general purpose optimization.
Marinho, Pedro Rafael D; Silva, Rodrigo B; Bourguignon, Marcelo; Cordeiro, Gauss M; Nadarajah, Saralees.
Afiliação
  • Marinho PRD; Department of Statistics, Federal University of Paraíba, João Pessoa, Paraíba, Brazil.
  • Silva RB; Department of Statistics, Federal University of Paraíba, João Pessoa, Paraíba, Brazil.
  • Bourguignon M; Department of Statistics, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
  • Cordeiro GM; Department of Statistics, Federal University of Pernambuco, Recife, Pernambuco, Brazil.
  • Nadarajah S; School of Mathematics, University of Manchester, Manchester, United Kingdom.
PLoS One ; 14(8): e0221487, 2019.
Article em En | MEDLINE | ID: mdl-31450236
Several lifetime distributions have played an important role to fit survival data. However, for some of these models, the computation of maximum likelihood estimators is quite difficult due to presence of flat regions in the search space, among other factors. Several well-known derivative-based optimization tools are unsuitable for obtaining such estimates. To circumvent this problem, we introduce the AdequacyModel computational library version 2.0.0 for the R statistical environment with two major contributions: a general optimization technique based on the Particle Swarm Optimization (PSO) method (with a minor modification of the original algorithm) and a set of statistical measures for assessment of the adequacy of the fitted model. This library is very useful for researchers in probability and statistics and has been cited in various papers in these areas. It serves as the basis for the Newdistns library (version 2.1) published in an impact journal in the area of computational statistics, see https://CRAN.R-project.org/package=Newdistns. It is also the basis of the Wrapped library (version 2.0), see https://CRAN.R-project.org/package=Wrapped. A third package making use of the AdequacyModel library can be found in https://CRAN.R-project.org/package=sglg. In addition, the proposed library has proved to be very useful for maximizing log-likelihood functions with complex search regions. The library provides a greater control of the optimization process by introducing a stop criterion based on a minimum number of iterations and the variance of a given proportion of optimal values. We emphasize that the new library can be used not only in statistics but in physics and mathematics as proved in several examples throughout the paper.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Probabilidade Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Probabilidade Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos