ZÁMEČNÍK, Stanislav, Ivanka HOROVÁ, Stanislav KATINA and Kamila HASILOVÁ. An adaptive method for bandwidth selection in circular kernel density estimation. Computational Statistics. Springer, 2023, vol. 39, No 4, p. 1709-1728. ISSN 0943-4062. Available from: https://dx.doi.org/10.1007/s00180-023-01401-0. |
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@article{2325437, author = {Zámečník, Stanislav and Horová, Ivanka and Katina, Stanislav and Hasilová, Kamila}, article_number = {4}, 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}, volume = {39}, 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 VL - 39 IS - 4 SP - 1709-1728 EP - 1709-1728 PB - Springer 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 and Kamila HASILOVÁ. An adaptive method for bandwidth selection in circular kernel density estimation. \textit{Computational Statistics}. Springer, 2023, vol.~39, No~4, p.~1709-1728. ISSN~0943-4062. Available from: https://dx.doi.org/10.1007/s00180-023-01401-0.
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