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A Truncated Pareto Model to Estimate the Under Recovery of Large Diamonds

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Abstract

The metallurgical recovery processes in diamond mining may, under certain circumstances, cause an under-recovery of large diamonds. In order to predict high quantiles or tail probabilities we use a Bayesian approach to fit a truncated Generalized Pareto Type distribution to the tail of the data consisting of the weights of individual diamonds. Based on the estimated tail probability, the expected number of diamonds larger than a specified weight can be estimated. The difference between the expected and observed frequencies of diamond weights above an upper threshold provides an estimate of the number of diamonds lost during the recovery process.

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Authors and Affiliations

  1. Department of Mathematical Statistics, University of the Free State, Bloemfontein, South Africa

    Andréhette Verster, Daan de Waal & Robert Schall

  2. Mineral Resource Management Department, De Beers Group Services, Johannesburg, South Africa

    Chris Prins

Authors
  1. Andréhette Verster
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  2. Daan de Waal
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  3. Robert Schall
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  4. Chris Prins
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Correspondence to Andréhette Verster.

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Verster, A., de Waal, D., Schall, R. et al. A Truncated Pareto Model to Estimate the Under Recovery of Large Diamonds. Math Geosci 44, 91–100 (2012). https://doi.org/10.1007/s11004-011-9374-1

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  • DOI: https://doi.org/10.1007/s11004-011-9374-1

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