15 citations · 19 across the 9 of their papers we have counts for
7 papers · 1 filter
Bridging the gap between experimental burden and statistical power for quantiles equivalence testing
Jun Wu, Stéphane Guerrier, Si Gou +2
Testing the equivalence of multiple quantiles between two populations is important in many scientific applications, such as clinical trials, where conventional mean-based methods m…
Bioequivalence Assessment for Locally Acting Drugs: A Framework for Feasible and Efficient Evaluation
Luca Insolia, Yanyuan Ma, Younes Boulaguiem +1
Equivalence testing plays a key role in several domains, such as the development of generic medical products, which are therapeutically equivalent to brand-name drugs but with redu…
Multivariate Adjustments for Average Equivalence Testing
Younes Boulaguiem, Luca Insolia, Maria-Pia Victoria-Feser +2
Multivariate (average) equivalence testing is widely used to assess whether the means of two conditions of interest are `equivalent' for different outcomes simultaneously. The mult…
Inference for Large Scale Regression Models with Dependent Errors
Lionel Voirol, Haotian Xu, Yuming Zhang +3
The exponential growth in data sizes and storage costs has brought considerable challenges to the data science community, requiring solutions to run learning methods on such data.…
Tk-merge: Computationally Efficient Robust Clustering Under General Assumptions
Luca Insolia, Domenico Perrotta
We address general-shaped clustering problems under very weak parametric assumptions with a two-step hybrid robust clustering algorithm based on trimmed k-means and hierarchical ag…
Doubly Robust Feature Selection with Mean and Variance Outlier Detection and Oracle Properties
Luca Insolia, Francesca Chiaromonte, Runze Li +1
We propose a general approach to handle data contaminations that might disrupt the performance of feature selection and estimation procedures for high-dimensional linear models. Sp…
Simultaneous Feature Selection and Outlier Detection with Optimality Guarantees
Luca Insolia, Ana Kenney, Francesca Chiaromonte +1
Sparse estimation methods capable of tolerating outliers have been broadly investigated in the last decade. We contribute to this research considering high-dimensional regression p…