collaborators

5 papers

math.ST2026

A spectral based coefficient of determination for the fit of an MA(q) model

Holger Dette, Sebastian Kühnert, Sebastian Kühnert

We develop a spectral based coefficient of determination to measure how well the spectral density of a stationary linear process is represented by the class of MA() models. Usin…

math.ST2026

Pivotal inference for linear predictions in stationary processes

Holger Dette, Sebastian Kühnert

In this paper we develop pivotal inference for the final (FPE) and relative final prediction error (RFPE) of linear forecasts in stationary processes. Our approach is based on a se…

stat.ME2026

An operator-level ARCH Model

Alexander Aue, Sebastian Kühnert, Gregory Rice +1

AutoRegressive Conditional Heteroscedasticity (ARCH) models are standard for modeling time series exhibiting volatility, with a rich literature in univariate and multivariate setti…

stat.ME2025

Functional Periodic ARMA Processes

Sebastian Kühnert, Juhyun Park

Periodicity is a common feature of time series. For finite-dimensional data, periodic autoregressive moving average (ARMA) models have been extensively studied. In functional time…

math.ST2025

Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes

Sebastian Kühnert, Gregory Rice, Alexander Aue

Invertible processes are central to functional time series analysis, making the estimation of their defining operators a key problem. While asymptotic error bounds have been establ…