QuEst gives point estimates and asymptotic confidence intervals for quantile-based distributional measures by optimally combining scarce observed data with abundant model-imputed data.
Arias, Samuel Lantei Mills, and Albert Motivans
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
QuEst gives point estimates and asymptotic confidence intervals for quantile-based distributional measures by optimally combining scarce observed data with abundant model-imputed data.