9 papers
Conditional Mean and Variance Estimation via \textit{k}-NN Algorithm with Automated Variance Selection
Marcos Matabuena, Juan C. Vidal, Oscar Hernan Madrid Padilla +1
We introduce a novel \textit{k}-nearest neighbor (\textit{k}-NN) regression method for joint estimation of the conditional mean and variance. The proposed algorithm preserves the c…
ROC Analysis with Covariate Adjustment Using Neural Network Models: Evaluating the Role of Age in the Physical Activity-Mortality Association
Ziad Akram Ali Hammouri, Yating Zou, Rahul Ghosal +2
The receiver operating characteristic (ROC) curve and its summary measure, the Area Under the Curve (AUC), are well-established tools for evaluating the efficacy of biomarkers in b…
Beyond Scalar Metrics: Functional Data Analysis of Postprandial Continuous Glucose Monitoring in the AEGIS Study
Marcos Matabuena, Joe Sartini, Francisco Gude
Postprandial glucose collected through continuous glucose monitoring (CGM) provides critical information for assessing metabolic capacity and guiding dietary recommendations. Tradi…
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi +2
Depth measures are powerful tools for defining level sets in emerging, non--standard, and complex random objects such as high-dimensional multivariate data, functional data, and ra…
Screening for Diabetes Mellitus in the U.S. Population Using Neural Network Models and Complex Survey Designs
Marcos Matabuena, Juan C. Vidal, Rahul Ghosal +1
Complex survey designs are commonly employed in many medical cohorts. In such scenarios, developing case-specific predictive risk score models that reflect the unique characteristi…
Optimal Cut-Point Estimation for Functional Digital Biomarkers: Application to Diabetes Risk Stratification via Continuous Glucose Monitoring
Oscar Lado-Baleato, Carla DÃaz-Louza, Francisco Gude +1
Establishing optimal cut-offs for clinical biomarkers is a fundamental statistical problem in epidemiology, clinical trials, and drug discovery. While there is extensive literature…