3 papers
stat.ME2026
An information criterion for detecting periodicities in functional time series
Rinka Sagawa, Yan Liu, Valentin Patilea
We propose an information criterion for determining an unknown number of periodic components in functional time series. Identifying the number of frequencies in large-scale time se…
stat.ME2025
Continuously updated estimation of conditional hazard functions
Daphné Aurouet, Valentin Patilea
Motivated by the need to analyze continuously updated data sets in the context of time-to-event modeling, we propose a novel nonparametric approach to estimate the conditional haza…
stat.ME2025
Discrete-time Markov chains with random observation times
Daphne Aurouet, Valentin Patilea
We propose a new approach for estimating the finite dimensional transition matrix of a Markov chain using a large number of independent sample paths observed at random times. The s…