Cubic rank transmuted distributions: inferential issues and applications (2017)
- Authors:
- Autor USP: LOUZADA NETO, FRANCISCO - ICMC
- Unidade: ICMC
- DOI: 10.1080/00949655.2017.1344239
- Subjects: ESTATÍSTICA; ESTATÍSTICA APLICADA; INFERÊNCIA BAYESIANA
- Keywords: Cubic transmutation; log-logistic distribution; maximum likelihood estimation; Weibull distribution
- Language: Inglês
- Imprenta:
- Publisher place: Philadelphia
- Date published: 2017
- Source:
- Título do periódico: Journal of Statistical Computation and Simulation
- ISSN: 0094-9655
- Volume/Número/Paginação/Ano: v. 87, n. 14, p. 2760-2778, 2017
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
GRANZOTTO, D. C. T e LOUZADA, Francisco e BALAKRISHNAN, N. Cubic rank transmuted distributions: inferential issues and applications. Journal of Statistical Computation and Simulation, v. 87, n. 14, p. 2760-2778, 2017Tradução . . Disponível em: https://doi.org/10.1080/00949655.2017.1344239. Acesso em: 23 abr. 2024. -
APA
Granzotto, D. C. T., Louzada, F., & Balakrishnan, N. (2017). Cubic rank transmuted distributions: inferential issues and applications. Journal of Statistical Computation and Simulation, 87( 14), 2760-2778. doi:10.1080/00949655.2017.1344239 -
NLM
Granzotto DCT, Louzada F, Balakrishnan N. Cubic rank transmuted distributions: inferential issues and applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 14): 2760-2778.[citado 2024 abr. 23 ] Available from: https://doi.org/10.1080/00949655.2017.1344239 -
Vancouver
Granzotto DCT, Louzada F, Balakrishnan N. Cubic rank transmuted distributions: inferential issues and applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 14): 2760-2778.[citado 2024 abr. 23 ] Available from: https://doi.org/10.1080/00949655.2017.1344239 - Cooperative parallel particle filters for online model selection and applications to urban mobility
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Informações sobre o DOI: 10.1080/00949655.2017.1344239 (Fonte: oaDOI API)
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