- Gazi University Journal of Science
- Vol: 33 Issue: 1
- A New Proposed Estimator for Reducing Bias Due to Undetected Species
A New Proposed Estimator for Reducing Bias Due to Undetected Species
Authors : Kürşad Özkan
Pages : 229-236
Doi:10.35378/gujs.554644
View : 8 | Download : 5
Publication Date : 2020-03-01
Article Type : Research
Abstract :The present paper addresses a new approach to reduce bias when there are undetected species in a plot. Partially density matrix plays essential role in this new proposed estimator. The performance of the new proposed estimator ( Ĥ 0 ) was compared to bias-corrected MLE (MLE BC ), Jackknife (JK) and the proposed estimator of Chao and Shen (Ĥ cs ) using Principle component analysis (PCA). The result of the first PCA applied to the data including the estimators’ values of the assemblages showed that Ĥ 0 is located between JK and Ĥ cs and its’ nearest neighbor becomes JK. The second PCA was applied to the data belonging to the relative estimator values between the pairwise assemblages and, it was found that Ĥ 0 is still located between JK and Ĥ cs but its’ nearest neighbor becomes Ĥ cs in this time along the first axis. Those results were evaluated that Ĥ 0 is a better estimator than MLE BC . Thus the new proposed estimator ( Ĥ 0 ) can also be used as an alternative bias-corrected estimator in addition to the other estimators.Keywords : Bias-corrected estimator, Diversity, Entropy, Jackknife, Partially density matrix