Context tree selection and linguistic rhythm retrieval from written texts (2012)
- Authors:
- USP affiliated authors: GALVES, JEFFERSON ANTONIO - IME ; LEONARDI, FLORENCIA GRACIELA - IME
- Unidade: IME
- DOI: 10.1214/11-AOAS511
- Assunto: CADEIAS DE MARKOV
- Keywords: Variable length Markov chains; model selection; BIC; smallest maximizer criterion; linguistic rhythm; European and Brazilian Portuguese
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Annals of Applied Statistics
- ISSN: 1932-6157
- Volume/Número/Paginação/Ano: v. 6, n. 1, p. 189-209, 2012
- Status:
- Artigo possui acesso gratuito no site do editor (Bronze Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
GALVES, Antonio et al. Context tree selection and linguistic rhythm retrieval from written texts. Annals of Applied Statistics, v. 6, n. 1, p. 189-209, 2012Tradução . . Disponível em: https://doi.org/10.1214/11-AOAS511. Acesso em: 07 maio 2026. -
APA
Galves, A., Galves, C., Garcia, J. E., Garcia, N. L., & Leonardi, F. G. (2012). Context tree selection and linguistic rhythm retrieval from written texts. Annals of Applied Statistics, 6( 1), 189-209. doi:10.1214/11-AOAS511 -
NLM
Galves A, Galves C, Garcia JE, Garcia NL, Leonardi FG. Context tree selection and linguistic rhythm retrieval from written texts [Internet]. Annals of Applied Statistics. 2012 ; 6( 1): 189-209.[citado 2026 maio 07 ] Available from: https://doi.org/10.1214/11-AOAS511 -
Vancouver
Galves A, Galves C, Garcia JE, Garcia NL, Leonardi FG. Context tree selection and linguistic rhythm retrieval from written texts [Internet]. Annals of Applied Statistics. 2012 ; 6( 1): 189-209.[citado 2026 maio 07 ] Available from: https://doi.org/10.1214/11-AOAS511 - Exponential inequalities for empirical unbounded context trees
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- Sequence motif identification and protein family classification using probabilistic trees
- Statistical model selection for stochastic systems with applications to bioinformatics, linguistics and neurobiology
- Consistent model selection for the degree corrected stochastic blockmodel
- Change point detection for high-dimensional regression data with l1-regularization
- Context tree selection: a unifying view
- Some upper bounds for the rate of convergence of penalized likelihood context tree estimators
- Computationally efficient change point detection for high-dimensional regression
- Nonparametric statistical inference for the context tree of a stationary ergodic process
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