7 papers
Compensator-based inference for signal detection under unknown background: the binned data case
Aritra Banerjee, Sara Algeri
The problem of signal detection under an unknown background can be framed as one of inferring the weight of a mixture model with one misspecified component. Banerjee and Algeri (20…
On the statistical analysis of grouped data: when Pearson and other divisible statistics are not goodness-of-fit tests
Sara Algeri, Estate V. Khmaladze
Thousands of experiments are analyzed, and papers are published each year involving the statistical analysis of grouped data. While this area of statistics is often perceived -- so…
A New Class of Asymptotically Distribution-Free Smooth Tests
Xiangyu Zhang, Sara Algeri
This article demonstrates how recent developments in the theory of empirical processes allow us to construct a new family of asymptotically distribution-free smooth tests. Their di…
Compensator-Based Inference for Signal Detection Under Unknown Background
Aritra Banerjee, Sara Algeri
The problem of detecting new signals in the presence of an unknown background is ubiquitous in scientific discoveries and is especially prominent in the physical sciences. Most sol…
A scalable Bayesian framework for galaxy emission line detection and redshift estimation
Alexander Kuhn, Bonnabelle Zabelle, Sara Algeri +2
Estimating galaxy redshifts is crucial for constraining key physical quantities like those in the equation of state of dark energy. Modern telescopes such as the James Webb Space T…
On Validating Angular Power Spectral Models for the Stochastic Gravitational-Wave Background Without Distributional Assumptions
Xiangyu Zhang, Erik Floden, Hongru Zhao +4
It is demonstrated that estimators of the angular power spectrum commonly used for the stochastic gravitational-wave background (SGWB) lack a closed-form analytical expression for…