We then used the best performing estimators to calculate relatedness coefficients for all pairs of individuals simultaneously entangled or captured, to be able to infer genealogical relationships.
Braun and Yuan [ 23] compared six different estimators of the variance, and Allignol et al. [ 13] demonstrated that the Greenwood-type estimator of the variance (Equation (6) in [ 13]) is algebraically equivalent to the top performing estimators in [ 23].
In addition, by mitigating the noise enhancement incurred in the LS estimator, the LMMSE estimator performs better than the LS estimator with the gain higher in the lower SNR region.
The simulation study shows that for a moderate sample size and selection probability, the IPW estimator and AIPW estimator perform better than the complete-case estimator.
Another algorithm, called Version B in [17] or LC-CFO in this article, is to add an additional step to Version A after performing the CFO estimator of (5).
The leave-one-out CoD estimator is the worst-performing estimator for cases with small number of predictors whereas the cross-validation CoD estimator becomes the worst-performing estimator for large number of predictors and moderate actual CoD.
Our results lead to a perhaps surprising conclusion: under the Zipf model under consideration, the resubstitution CoD estimator is the best-performing estimator among all, for moderate to large actual CoD and not too large number of predictors.
By observing the RMS, we conclude that the resubstitution CoD estimator is the best-performing estimator, except at small values of the actual CoD, beating all the other estimators, including the bootstrap.
Bootstrap 632 is a variant, which tries to correct the bias of the basic bootstrap estimator by performing an average with the resubstitution estimator [25]: (9).
