skbio.diversity.alpha.
lladser_ci
(counts, r, alpha=0.95, f=10, ci_type='ULCL')[source]¶Calculate single CI of the conditional uncovered probability.
State: Experimental as of 0.4.0.
counts (1-D array_like, int) – Vector of counts.
r (int) – Number of new colors that are required for the next prediction.
alpha (float, optional) – Desired confidence level.
f (float, optional) – Ratio between upper and lower bound.
ci_type ({'ULCL', 'ULCU', 'U', 'L'}) – Type of confidence interval. If 'ULCL'
, upper and lower bounds with
conservative lower bound. If 'ULCU'
, upper and lower bounds with
conservative upper bound. If 'U'
, upper bound only, lower bound
fixed to 0.0. If 'L'
, lower bound only, upper bound fixed to 1.0.
Confidence interval as (lower_bound, upper_bound)
.
tuple
See also
Notes
This function is just a wrapper around the full CI estimator described in Theorem 2 (iii) in 1, intended to be called for a single best CI estimate on a complete sample.
References
Lladser, Gouet, and Reeder, “Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown” PLoS 2011.