Algorithms to Calculate Exact Inclusion Probabilities for a Non-Rejective Approximate πpsSampling Design

• ZAIZAI YAN ^[1] ; YUXIA XUE ^[1]
  1. [1] Inner Mongolia University of Technology Science College
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 37, Nº. 1, 2014, págs. 127-140
• Idioma: inglés
• DOI: 10.15446/rce.v37n1.44362
• Títulos paralelos:
  • Algoritmos para calcular probabilidades exactas de inclusión para un diseño de muestreo no rechazable πpt
• Enlaces
  • Texto completo
• Resumen
  • español

    Una implementación del diseño de muestreo πpt, que no es de rechazo, ha sido recientemente propuesta como alternativa al esquema de Poisson. En este trabajo, hemos adaptado las formulas de probabilidades de inclusión en el diseño de muestreo Poisson alternativo (AP por sus siglas en inglés). Estas fórmulas han sido significativamente simplificadas. Los resultados propuestos muestran que el diseño AP y los algoritmos para calcular las probabilidades de inclusión son simples y efectivos, y que el diseño se puede usar en la práctica. Se incluyen tres ejemplos reales para ilustrar el desempeño de la propuesta.

  • English

    AP-design, an efficient non-rejective implementation of the πps sampling design, was proposed in the literature as an alternative Poisson sampling scheme. In this paper, we have updated inclusion probabilities formulas in the AP sampling design. The formulas of these inclusion probabilities have been greatly simplified. The proposed results show that the AP design and the algorithms to calculate inclusion probabilities are simple and effective, and the design is possible to be used in practice. Three real examples have also been included to illustrate the performance of these designs.

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