On identifiability of parametric statistical models

Autor:	Carlos Eduardo Pereira, Carlos Daniel Paulino
Rok vydání:	1994
Předmět:	Statistics and Probability Bayesian probability Econometrics Linear model Identifiability Statistical model Sample (statistics) PESQUISA E PLANEJAMENTO ESTATÍSTICO Statistics Probability and Uncertainty Bayesian inference Categorical variable Parametric statistics Mathematics
Zdroj:	Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP
ISSN:	1613-981X 1121-9130
DOI:	10.1007/bf02589044
Popis:	This is a review article on statistical identifiability. Besides the definition of the main concepts, we deal with several questions relevant to the statistician: parallelism between parametric identifiability and sample sufficiency; relationship of identifiability with measures of sample information and with the inferential concept of estimability; several strategies of making inferences in unidentifiable models with emphasis on the distinct behaviour of the classical and Bayesian approaches. The concepts, ideas and methods discussed are illustrated with simple examples of statistical models.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ff292e37d3b27e92d7a2f608fa8a598 https://doi.org/10.1007/bf02589044 Zobrazit plný text záznamu Full text from SpringerLink