Tests of exogeneity in proportional hazards models with censored data

Gilles Crommen, Jean-Pierre Florens, Ingrid Van Keilegom

A general framework for compound-Poisson INAR and INGARCH models

Barbora Sobolová, Johannes Bracher

Predictive inference for count data time series

Maxime Faymonville, Efstathios Paparoditis, Carsten Jentsch

Joint vector-autoregressive modeling of real- and integer-valued time series with full autoregressive parameter range

Carsten Jentsch, Maxime Faymonville, Miguel Kankeu Tedjouka

Absolute regularity of non-stationary count time series

Anne Leucht, Michael H. Neumann, Paul Doukhan

Covariate-adjusted Sensor Outputs for Structural Health Monitoring: A Functional Data Approach

Philipp Wittenberg

A Technical Note on Self-starting Regression Control Charts

Alessandro Di Bucchianico

Predictive Ratio Cusum (PRC): A Bayesian Approach in Online Change Point Detection of Short Runs

Konstantinos Bourazas, Frederic Sobas, Panagiotis Tsiamyrtzis

AI and the Future of Work in Analytics: insights from a first attempt to Augment ChatGPT and to assess the Quality of Generative AI Analytics capabilities

Inez Zwetsloot

Modern Extremes: Methods, Theories, and Algorithms

Johannes Lederer

Image classification: A new statistical viewpoint

Sophie Langer

Dropout Regularization Versus \ell_2-Penalization in the Linear Model

Gabriel Clara, Sophie Langer, Johannes Schmidt-Hieber

Inference on derivatives of high dimensional regression function with deep neural network(NN)

Weining Wang

Likelihood-based methods for low frequency diffusion data

Sven Wang, Matteo Giordano

Statistical guarantees for stochastic Metropolis-Hastings

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs

The Bernstein-von Mises theorem for semiparametric mixtures

Stefan Franssen, Jeanne Nguyen, Aad van der Vaart

Weak dependence and optimal quantitative self-normalized central limit theorems

Moritz Jirak

Recent advances in large sample correlation matrices and their applications

Johannes Heiny

Linear shrinkage for optimization in high dimensions

Theresia van Essen, Naqi Huang, Nestor Parolya

A test on the location of tangency portfolio for small sample size and singular covariance matrix

Svitlana Drin, Stepan Mazur, Stanislas Muhinyuza

Joint empirical risk minimization for instance-dependent positive-unlabeled data

Jan Mielniczuk, Wojciech Rejchel, Paweł Teisseyre

Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent

Michael Kohler, Adam Krzyzak

Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data

Miroslaw Pawlak

Advances in Adversarial Risk Analysis

Fabrizio Ruggeri

Modeling multivariate ordinal time series

Malte Jahn

Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence

Christian Weiß, Hee-Young Kim

Multivariate Motion Patterns and Applications to Rainfall Radar Data

Alexander Schnurr, Svenja Fischer, Marco Oesting

Depth patterns

Annika Betken, Alexander Schnurr

Hierarchical variable clustering based on the predictive strength between random vectors

Sebastian Fuchs, Yuping Wang

Kendall’s tau estimator for zero-inflated count data

Elisa Perrone, Edwin van den Heuvel, Zhuozhao Zhan

Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions

Rutger van der Spek, Alexis Derumigny

Inference via robust optimal transportation: theory and methods

Davide La Vecchia, Hang Liu, Matthieu Lerasle, Yiming Ma

Inference for topological data analysis

Wolfgang Polonik, Johannes Krebs, Benjamin Roycraft

Multi-study learning approaches

Roberta De Vito