High-dimensional copula-based dependence

Irène Gijbels, Steven De Keyser

Vine copulas for stochastic volatility

Alexander John McNeil

Sparse M-estimators in semi-parametric copula models

Jean-David Fermanian, Benjamin Poignard

Isotonic Distributional Regression - Likelihood Ratio Order and Total Positivity

Lutz Duembgen, Alexandre Moesching, Philip Stange

Single-index mixture cure model under monotonicity constraints

Eni Musta, Tsz Pang Yuen

Convex loss selection via score matching

Oliver Feng, Yu-Chun Kao, Min Xu, Richard J. Samworth

A comparison between Dirichlet process-based inference and shape-constrained inference for the Wicksell's inverse problem.

Francesco Gili

Multivariate functional additive mixed models

Alexander Volkmann, Almond Stöcker, Fabian Scheipl, Sonja Greven

Multivariate Functional Spatial Data: A Principal Component Analysis Approach

Sophie Dabo

Spatial Dependencies in Stock Returns

Dominik Wied

New STINARMA class of models in the analysis of space-time series of counts

Ana Martins, Manuel G. Scotto, Christian Weiß, Sónia Gouveia

A non-stationary spatio-temporal precipitation model for Austria

Corinna Perchtold, Johan Lindström, Evelyn Buckwar

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

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

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