Nonparametric, tuning-free estimation of S-shaped functions

Autor: Feng, OY, Chen, Y, Han, Q, Carroll, RJ, Samworth, RJ

We consider the nonparametric estimation of an S-shaped regression function. The least squares estimator provides a very natural, tuning-free approach, but results in a non-convex optimisation problem, since the inflection point is unknown. We show t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c84e5abe538b568214e8273250f2f059
https://www.repository.cam.ac.uk/handle/1810/336360

High-dimensional change point estimation via sparse projection

Autor: Wang, T, Samworth, RJ

Changepoints are a very common feature of Big Data that arrive in the form of a data stream. In this paper, we study high-dimensional time series in which, at certain time points, the mean structure changes in a sparse subset of the coordinates. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86890f2d3985311b1e2f079b960e2ceb
https://www.repository.cam.ac.uk/handle/1810/265277

Generalized additive and index models with shape constraints

Autor: Chen, Y, Samworth, RJ

We study generalised additive models, with shape restrictions (e.g. monotonicity, convexity, concavity) imposed on each component of the additive prediction function. We show that this framework facilitates a nonparametric estimator of each additive

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0d48e3cb8f94e65ff57e727f98653055
http://eprints.lse.ac.uk/65752/

Career intentions of medical students in the UK: a national, cross-sectional study (AIMS study).

Autor: Ferreira T; School of Clinical Medicine, University of Cambridge, Cambridge, UK tf385@cam.ac.uk., Collins AM; School of Public Health, Faculty of Medicine, Imperial College London, London, UK., Feng O; Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, UK., Samworth RJ; Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, UK., Horvath R; School of Clinical Medicine, University of Cambridge, Cambridge, UK.

Publikováno v: BMJ open [BMJ Open] 2023 Sep 12; Vol. 13 (9), pp. e075598. Date of Electronic Publication: 2023 Sep 12.

High-dimensional principal component analysis with heterogeneous missingness.

Autor: Zhu Z; Statistical Laboratory University of Cambridge Cambridge UK.; Department of Statistics University of Michigan Ann Arbor Michigan USA., Wang T; Statistical Laboratory University of Cambridge Cambridge UK.; Department of Statistics London School of Economics London UK., Samworth RJ; Statistical Laboratory University of Cambridge Cambridge UK.

Publikováno v: Journal of the Royal Statistical Society. Series B, Statistical methodology [J R Stat Soc Series B Stat Methodol] 2022 Nov; Vol. 84 (5), pp. 2000-2031. Date of Electronic Publication: 2022 Nov 20.