Hypothesis tests for Bernoulli experiments: ordering the sample space by Bayes factors and using adaptive significance levels for decisions (2017)
- Authors:
- USP affiliated authors: PEREIRA, CARLOS ALBERTO DE BRAGANCA - IME ; FOSSALUZA, VICTOR - IME ; ESTEVES, LUÍS GUSTAVO - IME
- Unidade: IME
- DOI: 10.3390/e19120696
- Assunto: ESTATÍSTICA APLICADA
- Keywords: significance level; sample size; Bayes factor; likelihood function; optimal decision; significance test
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
PEREIRA, Carlos Alberto de Bragança et al. Hypothesis tests for Bernoulli experiments: ordering the sample space by Bayes factors and using adaptive significance levels for decisions. Entropy, v. 19, n. 12, p. 1-15, 2017Tradução . . Disponível em: https://doi.org/10.3390/e19120696. Acesso em: 23 abr. 2024. -
APA
Pereira, C. A. de B., Nakano, E., Fossaluza, V., Esteves, L. G., Gannon, M., & Polpo, A. (2017). Hypothesis tests for Bernoulli experiments: ordering the sample space by Bayes factors and using adaptive significance levels for decisions. Entropy, 19( 12), 1-15. doi:10.3390/e19120696 -
NLM
Pereira CA de B, Nakano E, Fossaluza V, Esteves LG, Gannon M, Polpo A. Hypothesis tests for Bernoulli experiments: ordering the sample space by Bayes factors and using adaptive significance levels for decisions [Internet]. Entropy. 2017 ; 19( 12): 1-15.[citado 2024 abr. 23 ] Available from: https://doi.org/10.3390/e19120696 -
Vancouver
Pereira CA de B, Nakano E, Fossaluza V, Esteves LG, Gannon M, Polpo A. Hypothesis tests for Bernoulli experiments: ordering the sample space by Bayes factors and using adaptive significance levels for decisions [Internet]. Entropy. 2017 ; 19( 12): 1-15.[citado 2024 abr. 23 ] Available from: https://doi.org/10.3390/e19120696 - Estimating multivariate discrete distributions using Bernstein copulas
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Informações sobre o DOI: 10.3390/e19120696 (Fonte: oaDOI API)
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