activity
20052025
most citedShort-Term Load Forecasting: The Similar Shape Functional Time Series Predictor

103 citations · 319 across the 20 of their papers we have counts for

collaborators

23 papers

math.ST2025

Minimax testing in a statistical inverse problem with unknown operator

Clément Marteau, Theofanis Sapatinas

We study minimax testing in a statistical inverse problem when the associated operator is unknown. In particular, we consider observations from an inverse Gaussian regression model…

math.ST2020

Testing Equality of Spectral Density Operators for Functional Processes

Anne Leucht, Efstathios Paparoditis, Daniel Rademacher +1

The problem of comparing the entire second order structure of two functional processes is considered and a -type statistic for testing equality of the corresponding spectral d…

math.ST2019

Testing Equality of Autocovariance Operators for Functional Time Series

Dimitrios Pilavakis, Efstathios Paparoditis, Theofanis Sapatinas

We consider strictly stationary stochastic processes of Hilbert space-valued random variables and focus on fully functional tests for the equality of the lag-zero autocovariance op…

stat.ME2018★ 5 cited

Testing equality of spectral density operators for functional linear processes

Anne Leucht, Efstathios Paparoditis, Theofanis Sapatinas

The problem of testing equality of the entire second order structure of two independent functional linear processes is considered. A fully functional -type test is developed w…

math.ST2017

Moving Block and Tapered Block Bootstrap for Functional Time Series with an Application to the K-Sample Mean Problem

Dimitrios Pilavakis, Efstathios Paparoditis, Theofanis Sapatinas

We consider infinite-dimensional Hilbert space-valued random variables that are assumed to be temporal dependent in a broad sense. We prove a central limit theorem for the moving b…

math.ST2015★ 5 cited

Minimax Goodness-of-Fit Testing in Ill-Posed Inverse Problems with Partially Unknown Operators

Clément Marteau, Theofanis Sapatinas

We consider a Gaussian sequence model that contains ill-posed inverse problems as special cases. We assume that the associated operator is partially unknown in the sense that its s…