Research Software | Industrial Engineering & Management
Faculty member in the Department of Industrial Engineering and Management at Braude College of Engineering, Israel.
My research interests include statistical methodology, measurement science, agreement and reliability, categorical and ordinal data analysis, and operations research.
This GitHub profile provides open-source research software developed as part of my academic work, including Python implementations of statistical methods and tools for optimization and simulation.
The following repositories contain research software, documentation, and downloadable applications where available.
Agreement and reliability of categorical classifications
Research software for analyzing agreement between classifiers and exploring its metrological interpretation.
Related manuscript: Agreement Between Classifiers: A Metrological Interpretation — currently under peer review.
Appointment scheduling and simulation for medical services
A software tool for studying appointment scheduling and service operations, including simulation and scheduling analysis.
GitHub repository · Software DOI
Related publication:
Shnits, B., Bendavid, I., & Marmor, Y. N. (2020). An appointment scheduling policy for healthcare systems with parallel servers and pre-determined quality of service. Omega, 97, 102095. DOI.
Categorical and ordinal analysis of variance
A Python-based implementation of CATANOVA and ORDANOVA methods, including one-way and two-way analysis, Monte Carlo simulation, and graphical visualization.
GitHub repository · Download for Windows
Related publications:
- Gadrich, T., & Marmor, Y. N. (2021). Two-way ORDANOVA: Analyzing ordinal variation in a cross-balanced design. Journal of Statistical Planning and Inference. DOI.
- Gadrich, T., et al. (2024). Power of a test for assessing interlaboratory consensus of nominal and ordinal characteristics of a substance, material, or object. Metrologia. DOI.
Status: Research Preview — statistical validation in progress.
Detection of changes in sequential process behavior
A Python-based tool for detecting potential distributional changes over time using Anderson–Darling-based measures.
GitHub repository · Download for Windows
Related publication:
Marmor, Y. N., & Bashkansky, E. (2018). Abrupt change of process behavior: The Anderson-Darling detection tool. Quality Engineering, 30(2), 283–292. DOI.
Status: Research Preview — further methodological validation pending.
Distance between preference rankings, including ties
A Python-based research tool for comparing preference chains through cosine similarity and normalized angular distance.
GitHub repository · Download for Windows
Related publication:
Vanacore, A., Marmor, Y. N., & Bashkansky, E. (2019). Some metrological aspects of preferences expressed by prioritization of alternatives. Measurement, 135, 520–526. DOI.