Where does the indeterminacy come from?
Deriving the I of neutrosophic statistics from its sources
DOI:
https://doi.org/10.19139/soic-2310-5070-4832Keywords:
neutrosophic statistics, typed indeterminacy, provenance of uncertainty, interval data, imprecise probability, conflict between sources, hesitant sets, affine arithmeticAbstract
In neutrosophic statistics the indeterminate part I of an estimate is usually fixed by hand. We compute I from the records, once the analyst’s choices (confidence level, tolerance band, coding of undecided records) are declared, and split it into typed components with provenance: measurement imprecision, which more data do not remove; sampling, which they do; conflict between sources; and hesitancy. We give the exact split for counts and interval data, a test of certified conflict whose false-conflict rate is guaranteed under stated assumptions, the two readings of a hesitant set, a typed arithmetic that keeps the labels through operations, and a table of actions for each component, together with a step-by-step reporting protocol and a checklist. The inferential tools are classical; what is new is the labelled representation and reporting rule built on them, which we map explicitly to its counterparts in interval statistics, imprecise probability, belief functions and hesitant sets. A decision-oriented example shows what the labels can change: among 298 conversations whose majority safety verdict is undecided, the current estimates suggest different follow-up priorities, additional ratings for 229 and examination of the “unsure” answers for 60, a distinction that a single interval does not make; these priorities have not been validated as interventions. With imprecision alone, a fixed I amounts to an interval representation. A single fused interval hull does not retain the identities of disagreeing sources or distinguish the provenance of its width components; the labelled report makes this information explicit. As a conditional illustration, a paired batch-means test on daily rain forecasts from five weather models flags between-model conflict in Guayaquil in 53 % and 76 % of the 90- and 365-day windows and in no Santiago window; its assumptions cannot be verified here, and its level was supported only in simulated designs matched to a persistence diagnostic estimated from the same data, not at 30 days or under strong persistence. In the DICES safety ratings, absence of certified conflict is inconclusive because power is low.Downloads
Published
2026-11-02
How to Cite
Leyva Vázquez, M., & Smarandache, F. (2026). Where does the indeterminacy come from? Deriving the I of neutrosophic statistics from its sources. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-4832
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Copyright (c) 2026 Maikel Leyva Vázquez, Florentin Smarandache

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