116 citations · 117 across the 5 of their papers we have counts for
6 papers
Weak convergence of Bayes estimators under general loss functions
Robin Requadt, Housen Li, Axel Munk
We investigate the asymptotic behavior of parametric Bayes estimators under a broad class of loss functions that extend beyond the classical translation-invariant setting. To this…
Adaptive monotonicity testing in sublinear time
Housen Li, Zhi Liu, Axel Munk
Modern large-scale data analysis increasingly faces the challenge of achieving computational efficiency as well as statistical accuracy, as classical statistically efficient method…
Online jump and kink detection in segmented linear regression: Statistical optimality meets computational efficiency
Annika Hüselitz, Housen Li, Axel Munk
We consider the problem of sequential (online) estimation of a single change point in a piecewise linear regression model under a Gaussian setup. We demonstrate that certain CUSUM-…
Distributional limits of graph cuts on discretized grids
Leo Suchan, Housen Li, Axel Munk
Graph cuts are among the most prominent tools for clustering and classification analysis. While intensively studied from geometric and algorithmic perspectives, graph cut-based sta…
Robust inference of cooperative behaviour of multiple ion channels in voltage-clamp recordings
Robin Requadt, Manuel Fink, Patrick Kubica +3
Recent experimental studies have shed light on the intriguing possibility that ion channels exhibit cooperative behaviour. However, a comprehensive understanding of such cooperativ…
Consistencies and rates of convergence of jump-penalized least squares estimators
Leif Boysen, Angela Kempe, Volkmar Liebscher +2
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regression function by piecewise constant functions. Besides conventional consistency…