Estudo por simulação Monte Carlo de um estimador robusto utilizado na inferência de um modelo binomial contaminado

Content Provider	Semantic Scholar
Author	Silva, Augusto Maciel Da Cirillo, Marcelo Angelo
Copyright Year	2010
Abstract	A Monte Carlo simulation study of a robust estimator used in the inference of a contaminated binomial model. The statistical inference in binomial population is subject to gross errors of estimate, as the samples are not identically distributed. Due to this problem, this work aims to determine which is the best affinity constant (c1) that provides the best performance in the estimator, belonging to the class of E-estimators. With that purpose, the methodology used in this work was applied considering the Monte Carlo simulation method, in which different configurations described by combination of parametric values, levels of contamination and sample sizes were appraised. It was concluded that for the high probability of contamination (γ = 0.40), c1 = 0.1 is recommended in cases with large samples (n = 50 and n = 80).
Starting Page	303
Ending Page	307
Page Count	5
File Format	PDF HTM / HTML
DOI	10.4025/actascitechnol.v32i3.4145
Volume Number	32
Alternate Webpage(s)	http://periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/viewFile/4145/4145
Alternate Webpage(s)	https://doi.org/10.4025/actascitechnol.v32i3.4145
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article