15 citations · 24 across the 9 of their papers we have counts for
14 papers
Fatigue detection via sequential testing of biomechanical data using martingale statistic
Rupsa Basu, Katharina Proksch
Injuries to the knee joint are very common for long-distance and frequent runners, an issue which is often attributed to fatigue. We address the problem of fatigue detection from b…
Towards quantitative super-resolution microscopy: Molecular maps with statistical guarantees
Katharina Proksch, Frank Werner, Jan Keller-Findeisen +2
Quantifying the number of molecules from fluorescence microscopy measurements is an important topic in cell biology and medical research. In this work, we present a consecutive alg…
From Small Scales to Large Scales: Distance-to-Measure Density based Geometric Analysis of Complex Data
Katharina Proksch, Christoph Alexander Weitkamp, Thomas Staudt +2
How can we tell complex point clouds with different small scale characteristics apart, while disregarding global features? Can we find a suitable transformation of such data in a w…
Robust-to-outliers square-root LASSO, simultaneous inference with a MOM approach
G. Finocchio, A. Derumigny, K. Proksch
We consider the least-squares regression problem with unknown noise variance, where the observed data points are allowed to be corrupted by outliers. Building on the median-of-mean…
Simultaneous inference for Berkson errors-in-variables regression under fixed design
Katharina Proksch, Nicolai Bissantz, Hajo Holzmann
In various applications of regression analysis, in addition to errors in the dependent observations also errors in the predictor variables play a substantial role and need to be in…
Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
Christoph Alexander Weitkamp, Katharina Proksch, Carla Tameling +1
In this paper, we aim to provide a statistical theory for object matching based on the Gromov-Wasserstein distance. To this end, we model general objects as metric measure spaces.…
Tests for qualitative features in the random coefficients model
Fabian Dunker, Konstantin Eckle, Katharina Proksch +1
The random coefficients model is an extension of the linear regression model that allows for unobserved heterogeneity in the population by modeling the regression coefficients as r…
Risk Estimators for Choosing Regularization Parameters in Ill-Posed Problems - Properties and Limitations
Felix Lucka, Katharina Proksch, Christoph Brune +4
This paper discusses the properties of certain risk estimators recently proposed to choose regularization parameters in ill-posed problems. A simple approach is Stein's unbiased ri…
Multiscale scanning in inverse problems
Katharina Proksch, Frank Werner, Axel Munk
In this paper we propose a multiscale scanning method to determine active components of a quantity w.r.t. a dictionary from observations in an inverse regress…
Flaring of Blazars from an Analytical, Time-dependent Model for Combined Synchrotron and Synchrotron Self-Compton Radiative Losses of Multiple Ultrarelativistic Electron Populations
Christian Röken, Florian Schuppan, Katharina Proksch +1
We present a fully analytical, time-dependent leptonic one-zone model that describes a simplified radiation process of multiple interacting ultrarelativistic electron populations,…
Uncertainty Limits on Solutions of Inverse Problems over Multiple Orders of Magnitude using Bootstrap Methods: An Astroparticle Physics Example
Sabrina Einecke, Katharina Proksch, Nicolai Bissantz +2
Astroparticle experiments such as IceCube or MAGIC require a deconvolution of their measured data with respect to the response function of the detector to provide the distributions…
Multiscale inference for a multivariate density with applications to X-ray astronomy
Konstantin Eckle, Nicolai Bissantz, Holger Dette +2
In this paper we propose methods for inference of the geometric features of a multivariate density. Our approach uses multiscale tests for the monotonicity of the density at arbitr…
Confidence Corridors for Multivariate Generalized Quantile Regression
Shih-Kang Chao, Katharina Proksch, Holger Dette +1
We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for…
Confidence bands for multivariate and time dependent inverse regression models
Katharina Proksch, Nicolai Bissantz, Holger Dette
Uniform asymptotic confidence bands for a multivariate regression function in an inverse regression model with a convolution-type operator are constructed. The results are derived…