Version 1
: Received: 26 October 2022 / Approved: 31 October 2022 / Online: 31 October 2022 (04:53:43 CET)
How to cite:
Abdullahi, K.B. Some Estimators and their Properties Following Kabirian-based Optinalysis. Preprints2022, 2022100464. https://doi.org/10.20944/preprints202210.0464.v1
Abdullahi, K.B. Some Estimators and their Properties Following Kabirian-based Optinalysis. Preprints 2022, 2022100464. https://doi.org/10.20944/preprints202210.0464.v1
Abdullahi, K.B. Some Estimators and their Properties Following Kabirian-based Optinalysis. Preprints2022, 2022100464. https://doi.org/10.20944/preprints202210.0464.v1
APA Style
Abdullahi, K.B. (2022). Some Estimators and their Properties Following Kabirian-based Optinalysis. Preprints. https://doi.org/10.20944/preprints202210.0464.v1
Chicago/Turabian Style
Abdullahi, K.B. 2022 "Some Estimators and their Properties Following Kabirian-based Optinalysis" Preprints. https://doi.org/10.20944/preprints202210.0464.v1
Abstract
Good estimators are characterized as robust, unbiased, efficient, and consistent. However, the commonly used estimators are weak or lack one or more of these properties. In this article, eight (8) estimators for statistical and geometrical estimations of symmetry/asymmetry, similarity/dissimilarity, identity/unidentity, and feature transformation were proposed following Kabirian-based optinalysis and other operations. The proposed estimators are characterized as invariant (robust) under scaling, location shift, and rotation or reflection. A computing code was written in python language for each of the proposed estimators so that peers can have working codes for application and performance evaluation.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
