Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/39134
Título: Proposal of a bootstrap procedure using measures of influence in non-linear regression models with outliers
Título(s) alternativo(s): Proposta de um procedimento bootstrap utilizando medidas de influência em modelos de regressão não lineares na presença de outliers
Palavras-chave: CovRatio
Monte Carlo
Data do documento: 2014
Editor: Universidade Estadual de Maringá
Citação: ANDRADE, L. R. de; CIRILLO, M. A.; BEIJO, L. A. Proposal of a bootstrap procedure using measures of influence in non-linear regression models with outliers. Acta Scientiarum. Technology, Maringá, v. 36, n. 1, p. 93-97, Jan./Mar. 2014.
Resumo: The bootstrap method is generally performed by presupposing that each sample unit would show the same probability of being re-sampled. However, when a sample with outliers is taken into account, the empirical distribution generated by this method may be influenced, or rather, it may not accurately represent the original sample. Current study proposes a bootstrap algorithm that allows the use of measures of influence in the calculation of re-sampling probabilities. The method was reproduced in simulation scenarios taking into account the logistic growth curve model and the CovRatio measurement to evaluate the impact of an influential observation in the determinacy of the matrix of the co-variance of parameter estimates. In most cases, bias estimates were reduced. Consequently, the method is suitable to be used in non-linear models and allows the researcher to apply other measures for better bias reductions.
URI: http://repositorio.ufla.br/jspui/handle/1/39134
Aparece nas coleções:DEX - Artigos publicados em periódicos



Este item está licenciada sob uma Licença Creative Commons Creative Commons