A note on identifiability and maximum likelihood estimation for a heterogeneous capture-recapture model (2020)
- Authors:
- Autor USP: LOUZADA NETO, FRANCISCO - ICMC
- Unidade: ICMC
- DOI: 10.1080/03610926.2019.1615628
- Subjects: PROBABILIDADE APLICADA; ALGORITMOS ÚTEIS E ESPECÍFICOS; SIMULAÇÃO; REAMOSTRAGEM BOOTSTRAP
- Keywords: Capture-recapture; heterogeneity; identifiability; mixture model; population Size
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Communications in Statistics : Theory and Methods
- ISSN: 0361-0926
- Volume/Número/Paginação/Ano: v. 49, n. 21, p. 5273–5293, 2020
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PEZZOTT, George Lucas Moraes et al. A note on identifiability and maximum likelihood estimation for a heterogeneous capture-recapture model. Communications in Statistics : Theory and Methods, v. 49, n. 21, p. 5273–5293, 2020Tradução . . Disponível em: https://doi.org/10.1080/03610926.2019.1615628. Acesso em: 25 dez. 2025. -
APA
Pezzott, G. L. M., Salasar, L. E. B., Leite, J. G., & Louzada, F. (2020). A note on identifiability and maximum likelihood estimation for a heterogeneous capture-recapture model. Communications in Statistics : Theory and Methods, 49( 21), 5273–5293. doi:10.1080/03610926.2019.1615628 -
NLM
Pezzott GLM, Salasar LEB, Leite JG, Louzada F. A note on identifiability and maximum likelihood estimation for a heterogeneous capture-recapture model [Internet]. Communications in Statistics : Theory and Methods. 2020 ; 49( 21): 5273–5293.[citado 2025 dez. 25 ] Available from: https://doi.org/10.1080/03610926.2019.1615628 -
Vancouver
Pezzott GLM, Salasar LEB, Leite JG, Louzada F. A note on identifiability and maximum likelihood estimation for a heterogeneous capture-recapture model [Internet]. Communications in Statistics : Theory and Methods. 2020 ; 49( 21): 5273–5293.[citado 2025 dez. 25 ] Available from: https://doi.org/10.1080/03610926.2019.1615628 - Cooperative parallel particle filters for online model selection and applications to urban mobility
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Informações sobre o DOI: 10.1080/03610926.2019.1615628 (Fonte: oaDOI API)
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