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Revista Colombiana de Estadística
Print version ISSN 0120-1751
Rev.Colomb.Estad. vol.46 no.2 Bogotá July/Dec. 2023 Epub July 12, 2023
https://doi.org/10.15446/rce.v46n2.104591
Original articles of research
Some Improved Combined Estimators of Population Mean in Stratified Ranked Set Sampling
Algunos estimadores combinados mejorados de la media de la población en el muestreo de conjuntos clasificados estratificados
1 Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India
This paper presents improved population mean estimators using auxiliary variables in Stratified Ranked Set Sampling. We have derived the expressions for bias and mean square errors up to the first order of approximation and shown that the proposed estimators under optimum conditions are more efficient than other estimators taken in this paper. In an attempt to verify the efficiencies of proposed estimators, theoretical results are supported by numerical illustrations and simulation study for which we have considered two populations.
Key words: Auxiliary variable; Bias; Mean square error; Ranked set sampling; Study variable
Este artículo presenta estimadores mejorados de la media de la población utilizando variables auxiliares en el muestreo de conjuntos ordenados estratificados. Hemos derivado las expresiones para el sesgo y los errores cuadráticos medios hasta el primer orden de aproximación y hemos demostrado que los estimadores propuestos en condiciones óptimas son más eficientes que otros estimadores tomados en este artículo. En un intento por verificar las eficiencias de los estimadores propuestos, los resultados teóricos están respaldados por ilustraciones numéricas y estudios de simulación para los cuales hemos considerado dos poblaciones.
Palabras clave: Error cuadrático medio; Inclinación; Muestreo de conjuntos clasificados; Variable de estudio, Variable auxiliar
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Received: September 2022; Accepted: May 2023
This is an open-access article distributed under the terms of the Creative Commons Attribution License
