Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
권호 표지

A GENERALIZED MODEL-BASED OPTIMAL SAMPLE SELECTION METHOD

  • Hong, Ki-Hak (Department of Computer Science, Dongshin University) ;
  • Lee, Gi-Sung (Department of Computer Science & Statistics, Woosuk University) ;
  • Son, Chang-Kyoon (Department of Computer Science, Dongshin University)
  • Published : 2002.05.01

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Abstract

We consider a more general linear regression super-population model than the one of Chaudhuri and Stronger(1992) . We can find the same type of the best linear unbiased(BLU) predictor as that of Chaudhuri and Stenger and see that the optimal design is again a purposive one which prescribes choosing one of the samples of size n which has $\chi$ closest to $\bar{X}$.

Keywords

References

  1. Survey Sampling -theory and methods- A.Chaudhuri;H.Stenger
  2. Statistics & Probability Letters v.25 Improved predictors in survey sampling under a super-population model A.K.Srivastava
  3. Model Assisted Survey Sampling C.E.Sarndal;B.Swensson;J.H.Wretman
  4. Biometrika v.57 no.2 On finite sampling theory under certain linear regression models R.M.Royall
  5. Sampling Techniques W.G.Cochran