• Tutorial: Using QOD/OII Metric...

Treffer: Tutorial: Using QOD/OII Metrics in Python

Title:
Tutorial: Using QOD/OII Metrics in Python
Authors:
Tan, Kwan Hong, orcid:0009-0003-9276-
Publisher Information:
Zenodo
Publication Year:
2025
Collection:
Zenodo
Subject Terms:
Philosophy, Contemporary philosophy, Modern philosophy, ethics and religion, Metaphysics, Metaphysics/history, Ontology, Ontological Instability, Fluctuational Epistemology, Fluctuation Intensity, Correlation Dynamics, Phase Transition Probability, Emergence Potential, Ethical Responsivity, Quantitative Ontological Dynamics, QOD, Ontological Instability Index, OII, complex systems, Phase Transition, phase transitions, quantitative ontology, empirical philosophy, Python, Python Code
Document Type:
Fachzeitschrift text
Language:
English
Relation:
https://zenodo.org/records/17100822; oai:zenodo.org:17100822; https://doi.org/10.5281/zenodo.17100822
DOI:
10.5281/zenodo.17100822
Availability:
https://doi.org/10.5281/zenodo.17100822
https://zenodo.org/records/17100822
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode ; Copyright © 2025 Kwan Hong Tan
Accession Number:
edsbas.890C3069
Database:
BASE

Weitere Informationen

This tutorial shows how to compute Fluctuation Intensity (FI), Correlation Dynamics (CD), Phase Transition Probability (PTP), Emergence Potential (EP), and Ethical Responsivity (ER) using the QOD/OII framework. The code is based on three Python modules: ontological_metrics.py – core definitions of FI, CD, PTP, EP, ER financial_analysis.py – examples on financial time series (e.g. SPY, QQQ) comprehensive_analysis.py – end-to-end analysis pipeline Related Research: Tan, K. H. (2025). "Empirical Signatures of Ontological Instability: Quantifying Fluctuational Epistemology in Complex Systems." ResearchGate. https://www.researchgate.net/publication/394281660_Empirical_Signatures_of_Ontological_Instability_Quantifying_Fluctuational_Epistemology_in_Complex_Systems