estimatiit
Estimatiit is a hypothetical framework intended to illustrate approaches to collaborative estimation and uncertainty quantification in data-driven decision making. It envisions a system where individuals contribute estimates for uncertain quantities, annotate the underlying assumptions, and adjust their inputs as new information becomes available. The goal is to produce transparent, traceable estimates with quantified uncertainty.
In typical designs, estimatiit combines an input layer for point estimates and probability distributions with an
Methodologically, estimatiit emphasizes probabilistic thinking. It supports elicitation techniques to capture expert priors, uses update rules
Applications include collaborative forecasting, risk management, educational exercises in statistics, and strategic planning where multiple stakeholders
See also: Bayesian estimation, uncertainty quantification, Delphi method, crowdsourcing, participatory modeling.