Nonparametric Rotations for Sphere-Sphere Regression

Di Marzio, M, Panzera, A and Taylor, CC orcid.org/0000-0003-0181-1094 (2019) Nonparametric Rotations for Sphere-Sphere Regression. Journal of the American Statistical Association, 114 (525). pp. 466-476. ISSN 0162-1459

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 American Statistical Association. This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on 19 Jan 2018, available online: http://www.tandfonline.com/10.1080/01621459.2017.1421542. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Fisher's method of scoring; Local smoothing; Singular value decomposition; Skew-symmetric matrices; Spherical kernels; Wahba's problem
Dates:
  • Published: 2 January 2019
  • Accepted: 14 December 2017
  • Published (online): 19 January 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 18 Dec 2017 14:13
Last Modified: 21 May 2019 13:55
Status: Published
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/01621459.2017.1421542

Share / Export

Statistics