Další formáty:
BibTeX
LaTeX
RIS
@article{2325437,
author = {Zámečník, Stanislav and Horová, Ivanka and Katina, Stanislav and Hasilová, Kamila},
article_location = {HEIDELBERG, GERMANY},
doi = {http://dx.doi.org/10.1007/s00180-023-01401-0},
keywords = {Circular density; Bandwidth selector; Adaptive kernel estimator; Von Mises density; Smoothed cross validation},
language = {eng},
issn = {0943-4062},
journal = {Computational Statistics},
title = {An adaptive method for bandwidth selection in circular kernel density estimation},
url = {https://link.springer.com/article/10.1007/s00180-023-01401-0},
year = {2023}
}
TY - JOUR
ID - 2325437
AU - Zámečník, Stanislav - Horová, Ivanka - Katina, Stanislav - Hasilová, Kamila
PY - 2023
TI - An adaptive method for bandwidth selection in circular kernel density estimation
JF - Computational Statistics
PB - SPRINGER HEIDELBERG
SN - 09434062
KW - Circular density
KW - Bandwidth selector
KW - Adaptive kernel estimator
KW - Von Mises density
KW - Smoothed cross validation
UR - https://link.springer.com/article/10.1007/s00180-023-01401-0
N2 - Kernel density estimations of circular data are an effective type of nonparametric estimation. The performance of these estimations depends significantly on a smoothing parameter referred to as bandwidth. Selecting suitable bandwidths for these types of estimation pose fundamental challenges, therefore fixed bandwidth selectors are often the initial choice. The study investigates common bandwidth selection methods and proposes novel methods which adopt the idea from the linear case. The attention is also paid to variable bandwidth selection. Using simulations which incorporate a range of circular distributions that exhibit multimodality, peakedness and skewness, the proposed methods were evaluated and then compared with other bandwidth selectors to determine their potential advantages. Two real datasets, one containing animal movements and the other wind direction data, were applied to illustrate the utility of the proposed methods.
ER -
ZÁMEČNÍK, Stanislav, Ivanka HOROVÁ, Stanislav KATINA a Kamila HASILOVÁ. An adaptive method for bandwidth selection in circular kernel density estimation. \textit{Computational Statistics}. HEIDELBERG, GERMANY: SPRINGER HEIDELBERG, 2023, 20 s. ISSN~0943-4062. Dostupné z: https://dx.doi.org/10.1007/s00180-023-01401-0.
|
