Prior-free inferential models produce confidence intervals with exact nominal coverage for constrained parameters in normal and Poisson models with unknown nuisances, improved via random weighting for Poisson.
Communications in Statistics - Theory and Methods 53(6):2141–2153
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A continuum limit of superposed heterogeneous spin processes reproduces long-memory algebraic decay and generic growth in benthic algae population dynamics.
Ensemble learning with Gaussian copula transformation predicts groundwater heavy metal pollution index with high accuracy (R²=0.96) while identifying key contaminants via clustering.
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Constructing confidence intervals for constrained parameters via valid prior-free inferential models
Prior-free inferential models produce confidence intervals with exact nominal coverage for constrained parameters in normal and Poisson models with unknown nuisances, improved via random weighting for Poisson.
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Micro-macro population dynamics models of benthic algae with long-memory decay and generic growth
A continuum limit of superposed heterogeneous spin processes reproduces long-memory algebraic decay and generic growth in benthic algae population dynamics.
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Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
Ensemble learning with Gaussian copula transformation predicts groundwater heavy metal pollution index with high accuracy (R²=0.96) while identifying key contaminants via clustering.