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Optimum extrapolation and interpolation designs, I

  • J. Klefer
  • J. Wolfowitz
Article

Summary

For regression problems where observations may be taken at points in a set X which does not coincide with the set Y on which the regression function is of interest, we consider the problem of finding a design (allocation of observations) which minimizes the maximum over Y of the variance function (of estimated regression). Specific examples are calculated for one-dimensional polynomial regression when Y is much smaller than or much larger than X. A related problem of optimum estimation of two regression coefficients is studied. This paper contains proofs of results first announced at the 1962 Minneapolis Meeting of the Institute of Mathematical Statistics. No prior knowledge of design theory is needed to read this paper.

Keywords

Payoff Polynomial Interpolation Interpolation Problem Symmetric Design Chebyshev Approximation 
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

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Copyright information

© Institute of Statistical Mathematics 1964

Authors and Affiliations

  • J. Klefer
    • 1
  • J. Wolfowitz
    • 1
  1. 1.Cornell UniversityUSA

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