täpseimate
Täpseimate is a conceptual framework for producing precise estimates in the presence of uncertainty by merging multiple measurements and predictive models into a single calibrated estimate. It emphasizes both accuracy and reliable uncertainty quantification, aiming to deliver a point estimate accompanied by a well-calibrated interval of uncertainty.
At its core, täpseimate uses a weighted fusion of input estimates. Weights are learned from historical performance
Key methodological elements include estimating the uncertainty of each input, solving a constrained optimization that seeks
Applications span diverse areas such as sensor fusion, time-series forecasting, environmental monitoring, engineering quality control, finance
Relation to existing methods includes similarities to Bayesian model averaging and Kalman filtering, but täpseimate distinguishes