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On the histogram as a density estimator:L2 theory

  • David Freedman
  • Persi Diaconis
Article

Keywords

Stochastic Process Probability Theory Mathematical Biology Density Estimator 
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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  2. Cover, T.: A hierarchy of probability density function estimates. Frontiers of Pattern Recognition. New York: Academic Press 1972Google Scholar
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  4. Fryer, M.J.: A review of some non-parametric methods of density estimation. J. Inst. Math. Appl.20, 335–354 (1977)Google Scholar
  5. Knuth, D.: The Art of Computer Programming, Vol. 1, 2nd ed. Reading, Mass.: Addison-Wesley 1973Google Scholar
  6. Rosenblatt, M.: Curve estimates. Ann. Statist.2, 1815–1852 (1971)Google Scholar
  7. Scott, D.: On optimal and data-based histograms. Biometrika66, 605–610 (1979)Google Scholar
  8. Tapia, R.A., Thompson, J.R.: Nonparametric Probability Density Estimation. Baltimore: Johns Hopkins 1978Google Scholar
  9. Tarter, M.E., Kronmal, R.S.: An introduction to the implementation and theory of nonparametric density estimation Amer. Statist.30, 105–111 (1976)Google Scholar
  10. Wegman, E.J.: Nonparametric probability density estimation I. A summary of available methods. Technometrics14, 533–546 (1972)Google Scholar
  11. Wertz, W., Schneider, B.: Statistical density estimation: A bibliography. Internat. Statist Rev.47, 155–175 (1979)Google Scholar
  12. Woodroofe, M.: On choosing a delta sequence. Ann. Math. Statist.41, 1665–1671 (1968)Google Scholar

Copyright information

© Springer-Verlag 1981

Authors and Affiliations

  • David Freedman
    • 1
  • Persi Diaconis
    • 2
  1. 1.Statistics DepartmentUniversity of CaliforniaBerkeleyUSA
  2. 2.Statistics DepartmentStanford UniversityStanfordUSA

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