Draft:Deterministic–Probabilistic Utility Estimation Technique
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Comment: Fails WP:GNG, requires significant coverage in multiple independent verifiable secondary sources Dan arndt (talk) 08:13, 26 December 2025 (UTC)
 | This is a draft article. It is a work in progress open to editing by anyone. Please ensure core content policies are met before publishing it as a live Wikipedia article. Find sources: Google (books · news · scholar · free images · WP refs) · FENS · JSTOR · TWL Last edited by Dan arndt (talk | contribs) 5 months ago. (Update)
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Deterministic–Probabilistic Utility Estimation Technique (DUET) is an estimation framework for utility-based discrete choice models introduced in 2025 in the journal Transportation. It is presented as part of a bi-level approach in which an upper-level search selects transformations and interactions used to build an expanded feature library, and a lower-level procedure estimates coefficients and scale parameters using a combination of deterministic estimation and maximum-likelihood scaling.
References
- Ghorbani, Amir; Nassir, Neema; Sauri Lavieri, Patricia; Beeramoole, Prithvi Bhat; Paz, Alexander (2025). "Enhanced utility estimation algorithm for discrete choice models in travel demand forecasting". Transportation. doi:10.1007/s11116-024-10579-1.
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