Version 1
: Received: 23 May 2019 / Approved: 24 May 2019 / Online: 24 May 2019 (12:08:17 CEST)
Version 2
: Received: 12 November 2019 / Approved: 13 November 2019 / Online: 13 November 2019 (07:12:46 CET)
How to cite:
Abdullahi, K.B. Optinalysis: A New Approach of Multivariate Analysis through A Looking-Glass. Preprints2019, 2019050295. https://doi.org/10.20944/preprints201905.0295.v1
Abdullahi, K.B. Optinalysis: A New Approach of Multivariate Analysis through A Looking-Glass. Preprints 2019, 2019050295. https://doi.org/10.20944/preprints201905.0295.v1
Abdullahi, K.B. Optinalysis: A New Approach of Multivariate Analysis through A Looking-Glass. Preprints2019, 2019050295. https://doi.org/10.20944/preprints201905.0295.v1
APA Style
Abdullahi, K.B. (2019). Optinalysis: A New Approach of Multivariate Analysis through A Looking-Glass. Preprints. https://doi.org/10.20944/preprints201905.0295.v1
Chicago/Turabian Style
Abdullahi, K.B. 2019 "Optinalysis: A New Approach of Multivariate Analysis through A Looking-Glass" Preprints. https://doi.org/10.20944/preprints201905.0295.v1
Abstract
Optinalysis, as a method of symmetry detection, is a new advanced computational algorithm that intrametrically (within elements) or intermetrically (between elements) computes and compares two or more multivariate sequences in an unclustered or clustered manner as a mirror-like reflection of each other (optics-like manner), hence the name is driven. Optinalysis is based by the principles of reflection and moment about a symmetrical line which detects symmetry that reflects a similarity measurement. Optinalysis is suitable for quantitative and qualitative data types, with or without replications, provided it conform the algorithmic requirements there provided. Optinalysis can be organized for geometrical, geostatistical and statistical analysis in one-way, two-way, or three-way approach. A simulation comparisons shows that Optinalysis is a simple alternative approach of multivariate analysis of sociometric, demographic, socio-demographic, psychometric, ecological, experimental, genomic, nanoparticle and shape morphometric data. Optinalysis of these data matrix shows very similar results or conclusions with some multivariate analysis such as skewness measure, one-way ANOVA, paired t-test, one sample t-test, Tukey’s multiple comparisons, BLAST sequence algorithmic analysis (percentages of identity, similarity, gabs, and positives, and the Needleman-Wunsch score), and Riemannian distance.
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.
