Skip to main content

Abstract

Methods for local estimation of block recovery functions — b.r.f., based on bigaussian and multigaussian hypotheses, are analysed. The estimation methods were performed on a simulated deposit in order to compare their results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • — Journel, A. (1983) — Non-Parametric Estimation of Spatial Distribution. Math-Geology, Vol. 15, no. 3, pp. 445–468.

    Article  Google Scholar 

  • — Matheron, G. (1974) — Les Fonctions de Transfert des Petits Panneaux. Les Cahiers du Centre de Morphologie Mathématique de Fontainebleau, N-395, 73 p.

    Google Scholar 

  • — Verly, C. (1983) — The Multigaussian Approach and its Applications to the Estimation of Local Recoveries, in Math-Geology, Vol. 15 no. 2, pp. 263–290.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1984 D. Reidel Publishing Company

About this chapter

Cite this chapter

Soares, A. (1984). Local Estimation of the Block Recovery Functions. In: Verly, G., David, M., Journel, A.G., Marechal, A. (eds) Geostatistics for Natural Resources Characterization. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3699-7_28

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-3699-7_28

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-8157-3

  • Online ISBN: 978-94-009-3699-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics