3 papers
stat.ML2026
Multiclass Calibration Assessment and Recalibration of Probability Predictions via the Linear Log Odds Calibration Function
Amy Vennos, Xin Xing, Christopher T. Franck
Machine-generated probability predictions are essential in modern classification tasks such as image classification. A model is well calibrated when its predicted probabilities cor…
stat.ME2025
Scale-Location-Truncated Beta Regression: Expanding Beta Regression to Accommodate 0 and 1
Mingang Kim, Brent A. Kaplan, Mikhail N. Koffarnus +1
Beta regression is frequently used when the outcome variable y is bounded within a specific interval, transformed to the (0, 1) domain if necessary. However, standard beta regressi…
stat.ME2024
Thinking inside the bounds: Improved error distributions for indifference point data analysis and simulation via beta regression using common discounting functions
Mingang Kim, Mikhail N. Koffarnus, Christopher T Franck
Standard nonlinear regression is commonly used when modeling indifference points due to its ability to closely follow observed data, resulting in a good model fit. However, standar…