collaborators

5 papers

math.ST2026

False positive control in time series coincidence detection

Ruiting Liang, Samuel Dyson, Rina Foygel Barber +1

We study the problem of coincidence detection in time series data, where we aim to determine whether the appearance of simultaneous or near-simultaneous events in two time series i…

stat.ME2025

Mosaic inference on panel data

Asher Spector, Rina Foygel Barber, Emmanuel Candès

Analysis of panel data via linear regression is widespread across disciplines. To perform statistical inference, such analyses typically assume that clusters of observations are jo…

stat.ML2025

Assumption-free stability for ranking problems

Ruiting Liang, Jake A. Soloff, Rina Foygel Barber +1

In this work, we consider ranking problems among a finite set of candidates: for instance, selecting the top- items among a larger list of candidates or obtaining the full ranki…

stat.ME2025

Can a calibration metric be both testable and actionable?

Raphael Rossellini, Jake A. Soloff, Rina Foygel Barber +2

Forecast probabilities often serve as critical inputs for binary decision making. In such settings, calibration$\unicode{x2014}$ensuring forecasted probabilities match empirical fr…

math.ST2025

Are all models wrong? Fundamental limits in distribution-free empirical model falsification

Manuel M. Müller, Yuetian Luo, Rina Foygel Barber

In statistics and machine learning, when we train a fitted model on available data, we typically want to ensure that we are searching within a model class that contains at least on…