4 citations · 6 across the 3 of their papers we have counts for
3 papers
stat.ME2021★ 1 cited
Prediction in functional regression with discretely observed and noisy covariates
Siegfried Hörmann, Fatima Jammoul
In practice functional data are sampled on a discrete set of observation points and often susceptible to noise. We consider in this paper the setting where such data are used as ex…
stat.ME2020★ 1 cited
Preprocessing noisy functional data: a multivariate perspective
Siegfried Hörmann, Fatima Jammoul
We consider functional data which are measured on a discrete set of observation points. Often such data are measured with additional noise. We explore in this paper the factor stru…
math.ST2020★ 4 cited
Consistently recovering the signal from noisy functional data
Siegfried Hörmann, Fatima Jammoul
In practice most functional data cannot be recorded on a continuum, but rather at discrete time points. It is also quite common that these measurements come with an additive error,…