Finite population prediction under error in variables superpopulation models (1990)
- Autor:
- Autor USP: BOLFARINE, HELENO - IME
- Unidade: IME
- Assuntos: INFERÊNCIA BAYESIANA; ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
- Idioma: Inglês
- Imprenta:
-
ABNT
BOLFARINE, Heleno. Finite population prediction under error in variables superpopulation models. . São Paulo: IME-USP. Disponível em: https://repositorio.usp.br/directbitstream/f6098db9-956c-4baf-be60-a77f67a1c6a2/804388.pdf. Acesso em: 24 abr. 2024. , 1990 -
APA
Bolfarine, H. (1990). Finite population prediction under error in variables superpopulation models. São Paulo: IME-USP. Recuperado de https://repositorio.usp.br/directbitstream/f6098db9-956c-4baf-be60-a77f67a1c6a2/804388.pdf -
NLM
Bolfarine H. Finite population prediction under error in variables superpopulation models [Internet]. 1990 ;[citado 2024 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/f6098db9-956c-4baf-be60-a77f67a1c6a2/804388.pdf -
Vancouver
Bolfarine H. Finite population prediction under error in variables superpopulation models [Internet]. 1990 ;[citado 2024 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/f6098db9-956c-4baf-be60-a77f67a1c6a2/804388.pdf - Some shrinkage techniques for predicting the population total in finite populations
- Contribuições a teoria da previsão bayesiana e métodos relacionados em populações finitas
- Prediction in a finite population under a generalized linear model
- Inference under representable priors for Pearson type II models in finite populations
- Measurement error models with nonconstant covariance matrices
- Inference and local influence assessment in skew-normal null intercept measurement error model
- Large-sample inference for the Epsilon-Skew-t distribution
- Properties and Inference on the Skew-Curved-Symmetric Family of Distributions
- Multivariate measurement error models based on scale mixtures of the skew-normal distribution
- Bayesian estimation of regression parameters in elliptical measurement error models
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