Metrika

, Volume 33, Issue 1, pp 129–134 | Cite as

Estimation under linear regression models

  • P. Mukhopadhyay
Publications
  • 29 Downloads

Summary

Royall and Herson considered balanced samples for ensuring robustness of standard ratio estimator under polynomial superpopulation models. Here we formulate a post-sample estimator of Royall type which remains robust (in respect of bias) under a wide class of polynomial regression models.

Keywords

Linear Regression Regression Model Stochastic Process Probability Theory Economic Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Callebaut DK (1965) Generalisation of Cauchy-Schwartz inequality. Jour Math. Analysis and Applications 12:491–494CrossRefGoogle Scholar
  2. Mukhopadhyay P (1977) Robust estimators of finite population total under certain linear regression models. Sankhya, C 39:71–87Google Scholar
  3. Royall RM, Herson J (1973) Robust estimation in finite population I. Jour Amer Stat Assoc 68:880–889Google Scholar
  4. Scott AJ, Brewer KRW, Ho FWH (1978) Finite population sampling and robust estimation. Jour Amer Stat Assoc 73:359–361Google Scholar

Copyright information

© Physica-Verlag 1986

Authors and Affiliations

  • P. Mukhopadhyay
    • 1
  1. 1.Computer Science UnitIndian Statistical InstituteCalcuttaIndia

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