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Articole: 7
  1. Comparing diversity under collection bias

    True A : B– —–

  2. What Shall We Do with the Unseen Sailor?

    Bias in historical records At the Computational Humanities Research conference 2022 held in Antwerp from December 12 to 14, I co-presented a new paper with Melvin Wevers on missing data in historical archives.

  3. List of publications

    Books Kestemont, Mike, and Folgert Karsdorp. 2024.

  4. Estimating Unseen Shared Cultural Diversity

    Shared Species Estimation In Demystifying Chao1 with Good-Turing, I tried to explain the intuition behind the Chao1 estimator (Chao 1984) for unseen species using the Good-Turing estimator as described in Chao et al. (2017).

  5. Population Size Estimation as a Regression Problem

    Unseen heterogeneity Unseen Species Models such as Chao1 provide accurate point-estimates of the population size when the rare species in studied sample are homogeneous.

  6. Estimating Richness under Sampling without Replacement

    Unseen Species Models such as Chao1 assume that the sample being studied was created with replacement.

  7. Demystifying Chao1 with Good-Turing

    To estimate the “biodiversity” in a particular area – or, in other words, the number of unique species living in a given environment – ecologists usually have no other option than to rely on incomplete samples.