skbio.diversity.alpha.lladser_pe#

skbio.diversity.alpha.lladser_pe(counts, r=10, seed=None)[source]#

Calculate single point estimate of conditional uncovered probability.

Parameters:

counts1-D array_like, int: Vector of counts.
rint, optional: Number of new colors that are required for the next prediction.
seedint, Generator or RandomState, optional: A user-provided random seed or random generator instance. See details.

Added in version 0.6.3.

Returns:

double: Single point estimate of the conditional uncovered probability. May be np.nan if a point estimate could not be computed.

See also

lladser_ci

Notes

This function is just a wrapper around the full point estimator described in Theorem 2 (i) in [1], intended to be called for a single best estimate on a complete sample. This function is not guaranteed to return estimated uncovered probabilities less than 1 if the coverage is too low.

References

[1]

Lladser, Gouet, and Reeder, “Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown” PLoS 2011.