Estimation of a Finite Population Distribution Function

  • Parimal Mukhopadhyay
Part of the Lecture Notes in Statistics book series (LNS, volume 153)

Abstract

Estimation of a finite population distribution function has attracted considerable attention of survey statisticians over the last two decades. Our problem here is to estimate the finite population distribution function (d.f.)
$${{F}_{N}}(t) = \frac{1}{N}\sum\limits_{{i = 1}}^{N} {\Delta (t - {{y}_{i}})}$$
(6.1.1)
where Δ(z) is a step function with
$$\Delta (z) = 1(0) {\text{if}} z \geqslant 0 ({\text{otherwise),}}$$
on the basis of a sample s selected according to a sampling design p with selection probability p(s) and observations of the data.

Keywords

Sugar Covariance Income Cane Allo 

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Copyright information

© Springer-Verlag New York, Inc. 2001

Authors and Affiliations

  • Parimal Mukhopadhyay
    • 1
  1. 1.Applied Statistics UnitIndian Statistical InstituteCalcuttaIndia

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