39 citations · 122 across the 23 of their papers we have counts for
6 papers · 1 filter
Clustering multivariate functional data using unsupervised binary trees
Steven Golovkine, Nicolas Klutchnikoff, Valentin Patilea
We propose a model-based clustering algorithm for a general class of functional data for which the components could be curves or images. The random functional data realizations cou…
Learning the smoothness of noisy curves with application to online curve estimation
Steven Golovkine, Nicolas Klutchnikoff, Valentin Patilea
Combining information both within and across trajectories, we propose a simple estimator for the local regularity of the trajectories of a stochastic process. Independent trajector…
A presmoothing approach for estimation in semiparametric mixture cure models
Eni Musta, Valentin Patilea, Ingrid Van Keilegom
A challenge when dealing with survival analysis data is accounting for a cure fraction, meaning that some subjects will never experience the event of interest. Mixture cure models…
Wilks' theorem for semiparametric regressions with weakly dependent data
Marie Du Roy de Chaumaray, Matthieu Marbac, Valentin Patilea
The empirical likelihood inference is extended to a class of semiparametric models for stationary, weakly dependent series. A partially linear single-index regression is used for t…
Orthogonal Impulse Response Analysis in Presence of Time-Varying Covariance
Valentin Patilea, Hamdi Raïssi
In this paper the orthogonal impulse response functions (OIRF) are studied in the non-standard, though quite common, case where the covariance of the error vector is not constant i…
Modified Cox regression with current status data
Laurent Bordes, Maria Carmen Pardo, Christian Paroissin +1
In survival analysis, the lifetime under study is not always observed. In certain applications, for some individuals, the value of the lifetime is only known to be smaller or large…