Estimation of finite population distribution function with auxiliary information in a complex survey sampling
In this paper, we consider the problem of estimating the finite population cumulative distribution function (CDF) in a complex survey sampling, which includes two-stage and three-stage cluster sampling schemes with and without stratification. We propose two new families of CDF estimators using suppl...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/397829 |
| Acceso en línea: | https://hdl.handle.net/2117/397829 https://dx.doi.org/10.2436/20.8080.02.118 |
| Access Level: | acceso abierto |
| Palabra clave: | Sampling (Statistics) Mathematical statistics ratio estimator exponential ratio estimator auxiliary information stratification two-stage and three-stage cluster sampling relative efficiencies bias mean-squared error 62F Inferència paramètrica 62D05 Teoria del mostreig, enquestes de mostreig Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys Classificació AMS::62 Statistics::62F Parametric inference Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
| Sumario: | In this paper, we consider the problem of estimating the finite population cumulative distribution function (CDF) in a complex survey sampling, which includes two-stage and three-stage cluster sampling schemes with and without stratification. We propose two new families of CDF estimators using supplementary information on a single auxiliary variable. Explicit mathematical expressions of the biases and mean squared errors of the proposed CDF estimators are developed under the frst order of the approximation. Real datasets are also considered to support the proposed theory. |
|---|