5 citations · 6 across the 3 of their papers we have counts for
3 papers
stat.ME2023★ 1 cited
Maximum Agreement Linear Predictors
Taeho Kim, Pierre Chausse, Matteo Bottai +4
This paper studies predictor functions motivated by maximizing a measure of agreement with the predictand. Specifically, it examines distributional properties and predictive perfor…
stat.ME2020★ 5 cited
Prediction Regions for Poisson and Over-Dispersed Poisson Regression Models with Applications to Forecasting Number of Deaths during the COVID-19 Pandemic
T. KIm, B. Lieberman, G. Luta +1
Motivated by the current Coronavirus Disease (COVID-19) pandemic, which is due to the SARS-CoV-2 virus, and the important problem of forecasting daily deaths and cumulative deaths,…
stat.ML2020
A New Method to Compare the Interpretability of Rule-based Algorithms
Vincent Margot, George Luta
Interpretability is becoming increasingly important for predictive model analysis. Unfortunately, as remarked by many authors, there is still no consensus regarding this notion. Th…