Data/hora: 04/06/2024 18:23:44

Biblioteca(s): | Embrapa Unidades Centrais.
Data corrente: | 23/10/2003
Data da última atualização: | 12/04/2004
Autoria: | ARELLANO-VALLE, R. B.; OZAN, S.; BOLFARINE, H.; LACHOS, V. H.
Título: | Skew normal measurement error models.
Ano de publicação: | 2003
Fonte/Imprenta: | São Paulo,SP: USP-IME, 2003.
Páginas: | 21 p.
Série: | (Relatório Técnico, RT-MAE 2003-10).
Idioma: | Inglês
Conteúdo: | In this paper we define a class of skew normal measurement error models, extending usual symmetric normal in order to avoid data transformation. The likelihood function of the observed data is obtained, which can be maximized by using existing statistical software. Inference on the parameters of interest can be approached by using the observed information matrix, which can also be computed by using existing statistical software, such as the Ox program. Bayesian inference is also discussed for the family of asymmetric models in terms of invariance with respect to the symmetric normal distribution showng that early results obtained for the normal distribution also hosds for the asymmetric family. Results of a simulation study and an analysis of a real data set analysis are provided.
Palavras-Chave: | Invariance; Maximum likelihood; Posterior distribution; Prior distribution; Structural model.
Categoria do assunto: | --
Registro original: | Embrapa Unidades Centrais (AI-SEDE)
Exemplares: | AI-SEDE - (25007-1) - ADD - FL - -- - 01761 -  - 01761 - DIS