4 citations · 5 across the 17 of their papers we have counts for
4 papers · 1 filter
maars: Tidy Inference under the 'Models as Approximations' Framework in R
Riccardo Fogliato, Shamindra Shrotriya, Arun Kumar Kuchibhotla
Linear regression using ordinary least squares (OLS) is a critical part of every statistician's toolkit. In R, this is elegantly implemented via lm() and its related functions. How…
Nested Conformal Prediction Sets for Classification with Applications to Probation Data
Arun K. Kuchibhotla, Richard A. Berk
Risk assessments to help inform criminal justice decisions have been used in the United States since the 1920s. Over the past several years, statistical learning risk algorithms ha…
Valid Post-selection Inference in Assumption-lean Linear Regression
Arun Kumar Kuchibhotla, Lawrence D. Brown, Andreas Buja +2
Construction of valid statistical inference for estimators based on data-driven selection has received a lot of attention in the recent times. Berk et al. (2013) is possibly the fi…
Statistical Inference based on Bridge Divergences
Arun Kumar Kuchibhotla, Somabha Mukherjee, Ayanendranath Basu
M-estimators offer simple robust alternatives to the maximum likelihood estimator. Much of the robustness literature, however, has focused on the problems of location, location-sca…