Testing for sufficient follow-up in survival data with immunes

Tsz Pang Yuen, Eni Musta

Combining profile likelihood with Bayesian estimation for Crow-AMSAA process

Marek Skarupski

Optimizing the allocation of trials to sub-regions in multi-environment crop variety testing for the case of correlated genotype effects

Maryna Prus

Multivariate dependence based on diagonal sections with an application to welfare analysis

ANA PEREZ, MERCEDES PRIETO-ALAIZ, KOEN DECANCQ

Revisiting the Williamson transform in the context of multivariate Archimedean copulas

Nicolas Dietrich, Wolfgang Trutschnig, Thimo Kasper

Approximation of copulas using Cramér-von Mises statistic: regularization and model selection

Eckhard Liebscher

A Wasserstein perspective of Vanilla GANs

Lea Kunkel, Mathias Trabs

Asymptotic Theory for Constant Step Size Stochastic Gradient Descent

Jiaqi Li, Zhipeng Lou, Stefan Richter, Wei Biao Wu

A Continuous-time Stochastic Gradient Descent Method for Continuous Data

Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb

A Platform-Agnostic Deep Reinforcement Learning Framework for Effective Sim2Real Transfer in Autonomous Driving

Li Dianzhao, Ostap Okhrin

Adaptive factor modeling

Matthias Fengler

Fitting bivariate copula mixture models

Philipp Haid, Aleksey Min, Thomas Nagler, Yarema Okhrin

Instabilities in Time Dependent Functional Profiles: Theory and Computation

Matus Maciak, Sebastiano Vitali

Smoothing for a SIR process

Frank van der Meulen, Daniel Brus, Moritz Schauer

Nonparametric estimation of the interaction function in particle system models

Denis Belomestny, Mark Podolskij, Shi-Yuan Zhou

Statistical analysis of a stochastic boundary model for high-frequency data from a limit order book

Markus Bibinger

Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations

Shota Gugushvili

Statistical inference for intrinsic wavelet estimators of covariance matrices in a log-Euclidean manifold

Rainer von Sachs, Daniel Rademacher, Johannes Krebs

Time-Varying Covariance Matrices Estimation by Nonlinear Wavelet Thresholding in a Log-Euclidean Riemannian Manifold

Gabriel Bailly, Rainer von Sachs

Using High-Frequency Data to Improve Forecast Evaluation

Hajo Holzmann, Bernhard Klar

On the weak convergence of the function-indexed sequential empirical process for nonstationary time series

Florian Alexander Scholze

Towards a statistical foundation for machine learning methods

Johannes Schmidt-Hieber