RT Journal Article
T1 A reliable data-based smoothing parameter selection method for circular kernel estimation
A1 Ameijeiras Alonso, José
K1 Circular data
K1 Directional statistics
K1 Kernel density estimation
K1 Plug-in rule
K1 Sheather and Jones bandwidth
AB new data-based smoothing parameter for circular kernel density (and its derivatives) estimation is proposed. Following the plug-in ideas, unknown quantities on an optimal smoothing parameter are replaced by suitable estimates. This paper provides a circular version of the well-known Sheather and Jones bandwidths (J R Stat Soc Ser B Stat Methodol 53(3):683–690, 1991. https://doi.org/10.1111/j.2517-6161.1991.tb01857.x), with direct and solve-the-equation plug-in rules. Theoretical support for our developments, related to the asymptotic mean squared error of the estimator of the density, its derivatives, and its functionals, for circular data, are provided. The proposed selectors are compared with previous data-based smoothing parameters for circular kernel density estimation. This paper also contributes to the study of the optimal kernel for circular data. An illustration of the proposed plug-in rules is also shown using real data on the time of car accidents
PB Springer
SN 0960-3174
YR 2024
FD 2024
LK http://hdl.handle.net/10347/33860
UL http://hdl.handle.net/10347/33860
LA eng
NO Ameijeiras-Alonso, J. A reliable data-based smoothing parameter selection method for circular kernel estimation. Stat Comput 34, 73 (2024). https://doi.org/10.1007/s11222-024-10384-x
NO Supported by Grant PID2020-116587GB-I00 funded by MCIN/AEI/10.13039/501100011033 and the Competitive Reference Groups 2021-2024 (ED431C 2021/24) from the Xunta de Galicia. The author is grateful to Rosa M. Crujeiras and Alberto Rodríguez-Casal for helpful suggestions and comments. The author also expresses gratitude to three anonymous reviewers for providing valuable comments that significantly contributed to the enhancement of the paper. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature
DS Minerva
RD 22 abr 2026